Quintura CEO Yakov Sadchikov also reported,”We are announcing new tools and features of our hosted, visual-based site search and analytics solution, Quintura Site Search. The new features, which shall help online publishers to boost Click-Through-Rates (CTR) on both banners and search result links, include:

- Search Cloud Images: a new interface enables web publishers to embed images and banners (i.e. brand logos and advertisements) in the search cloud. When users mouse over an icon or search term, it expands into a banner, dramatically increasing the click-through rate in tests.

- Icon Blink: To attract users to images within the search cloud, we offer publishers customizable special effects, including blinking icons, to help boost Click-Through -Rates.

- Standalone Search Bar Option: The stand-alone search bar enables publishers to link Quintura Site Search to a separate web-page, so that when search terms are entered, a new window opens, displaying the full-range of search results.

- Color Customization – Additional color options allow web publishers to customize all aspects of the site search display, to match their web-site.

Source: Quintura Blog (Quintura is a sponsor of ours)

  Podcast 34:21m: Play Now | Play in Popup | Download

Rated PG-13

Since its creation in 2000, Exalead has striven to provide it users with an alternative path for exploring the Internet, to protect Internet users’ freedom of choice. To keep the massive amount of information users face both on the Web and at the office accessible and intelligible, we offer ample yet utterly simple tools for efficiently navigating and refining results and enjoyably exploring content. Traditional search engines, on the other hand, don’t give users a choice beyond simply clicking < Next > to move on to the next page in an infinite laundry list. However, we’ve been highly pleased to see that our approach, which we call “Search by Serendipity,” is being taken up bit by bit by the heavyweights.

For all but the simplest navigational searches, too much time is spent trying to find the magic query that yields the desired information on the first page of search results. The search engine should actively work with the user to help them find what they need.


How do you define both explicit and implicit personalization?
With explicit personalization, the user in the driver’s seat. Within the limits of the available tools, users can customize and filter resources on a site in the manner that best suits their needs.

With implicit personalization, it is the site itself that adapts and conforms independently to the needs of the user. It can automatically adapt its resources to the needs of a user (whether individually or as part of a user group) based on the user’s profile and prior behavior.

Our search platform incorporates elements of both types of personalization. Through our public Web engine, we propose a wealth of explicit personalization options for our users, responding as effectively as we can to the heterogeneity of the Web and Web users. For B2C portals deploying our search engine on their own sites, we offer a number of implicit personalization tools as well. These types of tools are best suited to a more homogeneous audience and content base, with the expectations and needs of users being easier to identify-and hence leverage-in the quest for an improved user experience.

Speretta and Gauch wrote “Personalization is the process of presenting the right information to the right user at the right time.” Explicit and implicit personalization are two non-exclusive and complementary implementations.

Explicit personalization specifically asks the user to provide more information about their information need(s). This information is sometimes gathered through long-term general interest surveys (e.g. “what are your hobbies, what is your profession, where do you live?”). For specific information seeking tasks, explicit personalization sometimes asks the user to narrow the search via drill-down menus or by selecting information clusters. In classical information retrieval research, explicit relevance feedback is a technique where the searcher is asked to manually rate documents they have seen in order to more accurately fetch additional documents. Information directly gathered from the user is very powerful for tailoring a search session to the specific user.

Implicit personalization relies on the more ambiguous but more easily obtained history of user behavior to indirectly infer the user’s information need(s). Implicit personalization can be long term (e.g. a person’s hobbies can often be inferred from the web sites they visit repeatedly) or short term (a person’s immediate information need can be inferred from their current actions and context). Implicit personalization can also be collective (e.g. your friends like this so you may be interested in it). Although each user action is only weakly correlated with their long-term interests, the combination of multiple weak signals can lead to very powerful inferences. Properly interpreted, user behavior can lead to strong conclusions about the user’s short-term interests.

What are some popular examples?

Exalead.com is a good example of explicit personalization. All users are presented with the same result sets based on their query keywords, but the presentation makes extended use of keyword clustering to allow users to personalize these result sets based on their needs and interests. We deployed clustering in advance of Ask, and even Google, setting trends in this as well as other areas of Web search technology.

An example of implicit personalization is Last.fm. Last.fm shows that the implicit web is already a reality. Last.fm recommends new music to a user by independently analyzing the user’s existing library of favorite artists. Our purchases, our navigation histories and our search queries feed these types of recommendation engines and can help them refine the World Wide Web for us.

In the context of search, popular examples of explicit personalization are geo-targeting through IP addresses (e.g. if you search for “Ford” he advertisements will often be for local car dealers), related query suggestion (Yahoo! Search Suggest), categorical and hierarchical rill-down (Exalead, Clusty, Endeca, etc.), and explicit user profiling (when Netflix asks you to rank movies that you have seen).

Implicit personalization is used by Google (when you have activated the option) to provide a few search results that take into account your rowsing history. Amazon suggestions are based on implicit personalization although the suggestions are often humorous if you are like me and share an account with your spouse. Surf Canyon is the first company to provide real-time implicit personalization.

What are some of the major advantages and disadvantages of explicit personalization?

The freedom to explore, a uniform user experience. When resources are not filtered according to a user’s prior actions, then that user retains total liberty to explore and discover the complete universe of content available to them. A standardized, non-personalized presentation of resources also constitutes a shared, even egalitarian experience, with each click guiding users to the same results. On the other hand, leaving personalization options solely in the hands of the user can make it more difficult for him or her to fulfill their needs because the system cannot capitalize on a user’s prior actions to help divine their intentions and guide them through what is often an overwhelming amount of information.

The advantage of explicit personalization is that the information is unambiguous. When the user selects a related query or chooses a category among the possibilities presented, the search becomes much more accurate.

The largest hurdle for explicit personalization is that it requires additional work on the part of the user. Web users are overwhelmed by requests for our attention and often don’t want to exert additional effort even if it provides real benefit.

Another major disadvantage is that a user might not be fully cognizant of what they are looking for. If I am using a search engine with categorization, I might end up in the wrong category before I know enough to select the correct category. Even worse, any system that requires the user to explicitly profile themselves is susceptible to people describing who they want to be rather than who they are. As Jason Fry wrote in the Wall Street Journal, “…we lie — and never more effectively than when we’re lying to ourselves. My dissatisfaction with Amazon’s recommendations may have more to do with my view of myself than it does with Amazon’s engine: I fancy myself a reader of contemporary literature and history books, but I mostly buy “Star Wars” novels and “Curious George” books for my kid.”

What are some of the major advantages and disadvantages with implicit personalization?


This interesting approach points to one of the great paradoxes of the Web as revealed by our 2007 study: while 80% of the participants expressed a desire for personalized content, 50% evinced a strong resistance to divulging personal information in exchange.

We think implicit personalization is not well adapted for use in general Web search, if it is offered in isolation. The world of the Internet is infinite and deeply heterogeneous, and the behaviors of individual users are not really predictable. If I search on “leopard,” am I looking for a picture for my kid’s school report, or for information on the latest Mac OS?

On the other hand, the use of implicit personalization is very interesting in more constrained contexts. Our enterprise search software for portals (e-commerce, community sites, content portals, etc.) provide the intelligence needed to deploy implicit personalization and therefore to improve the user experience and augment site revenue.

Of course, implicit personalization raises privacy concerns. Users are rightly concerned as to whether the data they provide or their patterns of navigation for a particular site will be exploited in an unwelcome manner in another context.

The major advantage of implicit personalization is that it requires no additional effort on the part of the user. When implemented properly it can be very effective in providing accurate recommendations to the user.

The major disadvantage of implicit personalization is that it can sometimes make incorrect inferences, especially when the data is sparse or when the user context changes. My long-term interests may be at odds with my short term information needs. As an example, if I search for “Giants Stadium” and hail from San Francisco I am much more likely interested in the place where San Francisco Giants play (I have forgotten the stadium ame since they seem to have a new sponsor every year). Next fall, however, I might find myself in New York and interested in the parking at the Meadowlands.

Surf Canyon does implicit personalization in real time, and the sparse data problem is something we work to overcome. Fortunately, for the most difficult searches we often have the greatest amount of user behavior data and can therefore be of greatest benefit.

Which has the greatest potential to improve the search experience?


They both have great potential to improve the search experience, but only if they are always presented in a transparent manner, with the user retaining the right to choose one type or the other according to the usage context. Again, our approach to Web search rests on leaving choice in the hands of the user, and on respect for users’ privacy.

Both forms of personalization have great potential for improving the search experience, and even more so if used together! For the majority of queries, personalization in any form is unnecessary. The search engine has essentially replaced URLs and bookmarks for navigating to websites, and personalization does nothing for these navigational queries. If the user doesn’t end their search session with the first click, implicit Real-time personalization should begin working with the user to help them find what they need. At the same time, explicit personalization options should be made available to further help the search. Different Searches will require different tools. As the volume of web content grows, users will demand access to all of these tools.

There are many challenges, but fundamentally these are the same for search engines in any vertical: finding and adding fresh content; identifying and removing bad content; accounting for duplicate data; processing search queries quickly. If you’ve solved the fundamental problems, then you can apply them to any vertical without too much trouble. Properazzi are already very advanced down this path already in real estate, with technology that indexes 4 million listings from 11,000 different agency websites.

The main challenge for a property search engine is a variation of the general problem faced by many disruptive start-ups: How do you make yourself known and differentiate yourself when there are powerful web 1.0 property incumbents already online? There are obvious differences between property search engines and web 1.0 real estate portals, but how do you convince consumers that they should care? A lot of consumers are already accustomed to behemoth companies like Rightmove in the UK (a listed company with a market cap of more than €1 billion) or Seloger in France (also a listed company with a market cap upwards of €700 million), and these companies have enough money to out-spend us and enough brand recognition to pose a significant entry barrier. In addition, vertical search engines aren’t a particularly viral product like Facebook where customers have an obvious incentive to return every day and share it with all of their friends. 

So getting the customer to the product is the main challenge when there are powerful incumbents with well-established brands who don’t have cutting-edge products but their products are still more-or-less okay for the average Internet user. Once the customer gets to our product, it’s fairly easy for her to understand how a property search engine like nuroa will make her life a lot easier and disrupt her prior real estate search experience. But the main initial challenge is getting her there. Other than that, there are specific problems related to making sure that our results are precise, relevant and exhaustive, which can be a challenge given that the quality of the underlying property web sites in each country are sometimes pretty questionable.

2.  AltSearchEngines has come across seven significant Property Search Engines in your area, and other minor ones. Why such a crowded field? Are you all primarily similar, or fundamentally different?

In the past few years I’ve seen lots of projects in this area, probably motivated by the promise of easy money: just combine real estate (money!) with the Google business model (more money!) with the mashup/search engine template (easy!). So there was economic motivation and a low perceived entry barrier. If anything, I’m surprised there haven’t been many more startups in the field…maybe what’s missing in the mix is some social networking (sexy!)

Vertical search is a good, simple yet intuitive idea that no one was doing it Europe. That companies like News Corp, The New York Times and Sequoia have invested in similar products in the US (and now in Europe) further encourages European entrepreneurs to start similar local projects before the Americans arrive. As for differences among vertical search engines, it all depends on how closely you look. On some level, Google and Yahoo both have search engines, but they are not regarded as the same. Similarly, on a very basic level, we’re all search engines focused on property. But many of us operate in different markets. For example, Globrix is not currently nuroa’s direct competitor. Their market is the UK, and their main competition is in the UK — nuroa is focused currently on Germany and Spain. Each market is a different world with its own rules, home-buying and renting patterns, economic evolution, language, competitors and targets.

Apart from geography, some of us have different objectives. nuroa aims to be profoundly local — Spaniards buying properties in Spain, and Germans buying properties in Germany — whereas Properazzi has a much more international focus and scope from the beginning. On a technical level, we sometimes differ on how we obtain the property ads. Some of us rely more on receiving XML feeds, whereas others focus more on search technology. Then as an empirical matter, there are obviously going to be differences in whose results are more precise and exhaustive with a higher degree of recall, and the breadth and quality of the results will probably be the key differentiator from the consumer’s point of view. And finally, there are “softer” issues like usability and design that also affect the user experience. That being said, I’m pretty sure that we all borrow and learn from one another.

3.  Most of the updates that we receive from your space are larger territories covered, which is natural, but where does it end for you? How much geography do you seek to cover in the end?

The world, of course! Properazzi never made any secret of its ambition to be the platform for the world’s property listings. Since launching in March 2007, Properazzi have been steadily adding new markets, and now cover 50 countries. We’ll continue to add support for further countries in 2008. But geography is not the only axis along which Properazzi are planning to expand near term.

To date, the web 1.0 real estate portals have been quite successful even though they only operate in one geographical market (this goes back to my answer above about whether those of us who currently operate in different markets will necessarily have to compete against one other at some later point). Rightmove’s expansion plan is to cover all of the UK as opposed to just the big cities like London.

For the moment, they’ve felt no need to compete vigorously outside of the UK. Seloger has a similar strategy to increase its penetration in the provinces outside of Paris. As mentioned above, Rightmove has a market cap of more than €1 billion, and Seloger is close with a market cap of more than €700 million. So you can create an interesting business in just one geographical market if you can become the market leader. That being said, our search technology in nuroa is obviously very scalable, so you can easily adapt it to new countries and even to new verticals. As with most things, your limits will depend to some extent on your financing and your ability to execute.

4.  Can you just summarize your business model and how it relates to the financial needs of the real estate agents/brokers, and perhaps even the property searchers and/or sellers?

Our business model is advertising. It’s great for the advertisers because we’re delivering a very high-value audience for much lower cost than they’re used to paying. For property buyers/renters, Properazzi is 100% free, so our model works great for them as well.

We make money via advertising — featured listings, banners, etc. The web 1.0 real estate portals require real estate agents/brokers to pay a set monthly fee to upload a predetermined number of listings regardless of whether the site actually generates leads for the real estate agency. And given that most of these portals only intend to grow within their national boundaries (and some are public companies), the only ways for them to grow are up and out — up, meaning that they will have to raise prices as many have done over the past year, in some cases doubling the prices; and out, meaning out of the big cities where they started and into the more remote provinces within their geographic market.

Nuroa’s model is different — more pay per click than subscription fee: an agency only pays if we send them traffic for a featured listing or some other form of sponsored ad/banner. Agents don’t have to pay us to have their listings show up organically on our site. From the consumers’ perspective, it’s very useful to have all or most of the property ads in nuroa. Classifieds sites are growing like mushrooms as print continues to falter and more traditional media companies move online, and no one has the time or attention span to visit 50 sites to look for her perfect property. A property search engine cuts out all of the unnecessary steps and let’s the user find her dream home in a couple of clicks.

5.  What is your relationship to the major search engines, Google, Yahoo!, et al? Are they your major concern – or are your fellow Property search engines your main rivals for business?

I honestly think it’s too early days to answer this question effectively. As we evolve, it’s just not clear yet who ends up being a partner, a competitor, or simply a “not relevant”. Ask me again in two or three years

Our goal is to supplement not supplant Google and the other major search engines. We don’t really see them as our competition. Google had Google Base for a while, but they don’t really seem to have pushed it very hard. And last year TechCrunch reported that Google was in talks to buy SimplyHired, so obviously that means that, if the reports are true, Google sees the opportunity in vertical search and isn’t opposed to purchasing the market-leader in each vertical. That being said, we didn’t start this company hoping to be bought by Google. Not that we’d be opposed to it on principle, but nuroa’s goal is to become the next Rightmove or the next Seloger. And we see our fellow property search engines within our geographical markets as our most immediate competitors.

6.  How do you market your site – drive users to you as opposed to anywhere else?

We dabble in most of the usual marketing type of activities, but work hardest on developing a great product for users so they can remember and return to our site, and recommend it to their friends.

As mentioned above, this is our main challenge. And we take a variety of approaches to marketing our product, though I’d probably prefer not to explain our strategic marketing plan in any great amount of detail. But I can say that it’s a combination of SEO, SEM and viral marketing.

7.  It’s a tradition to say something complimentary about your debate partner.

Migoa: nice integration of flickr and technorati data, and they chose a great city in which to be based.

In the case of Properazzi, I’d say that we learned a lot from them. They launched before we did and provided a key test case for seeing the market’s reaction and adapting our own strategy before launching. They were also the first European vertical search engine to receive funding from a major European VC, so that served as an inspiration to us. 

Tonight’s debate is on the topic of consumer electronics search engines.  Our participants are Robb with Retrevo and Syed from ShoppingVale.

 1.  A consumer wants to buy their spouse a digital camera for Christmas.
Why should they go to your search engine instead of a major search engine or a store’s website?

Each has different problems so let me address them separately. General search engines such as Google or Yahoo return many results but leave it up to the user to sift through them to determine which ones matter. Because general search engines heavily weight referral links most of the results are all pricing engines because many, many sites link to them for price shopping. Great if the shopper already knows the specific product they want but how does that help consumers DISCOVER the right product that isn’t based on just price or a spec list of features consumers don’t understand?

As for starting at a retailer, well unfortunately for them the Internet has significantly disrupted their role of influencing a consumer’s product decision. A single retailer just can’t offer all the products in a given category so they only present a small sub-set of pre-selected brands and models. Retailers just don’t have the depth of products and their information is often a subset of what the manufacturer has available or quite often incorrect when compared to the actual product manufacturer. Further, how does a consumer know the retailer isn’t pushing products the reps are spiffed or give the store the most profit rather than recommending products that best fit the consumer’s needs?

Retrevo goes beyond search and algorithmically ANALYZES information and presents products in a simple, easy to understand assessment that helps them find the right product and feel confident about the product they want to buy. The Retrevo Product Advisor helps consumers discover products that match their interests simply and easily. When a user first lands on the Product Advisor page they see a real-time view of what to expect for the product category. We break each product category into three simple groups – Low-end, Mid-range and High-end. This helps simplify the information for consumers into something they can easily and quickly digest. Not only does it simplify understanding a product category it’s also the ONLY report that changes in real-time to reflect current market conditions. As new products are introduced or price changes occur, our “what to expect” lists adjust automatically. Products that were once rated high-end or mid-range just six months ago may now be mid-range and low-end products. This is the most accurate and up to date view of any consumer electronics product category in the industry.

Consumers can narrow their search by providing input as to their interests. For each product we have generated a profile that gives users the main points (the “gist”) of any product. This allows consumers to quickly understand the pertinent points they should know and assess if a product is a good product to buy or spend time looking at details such as reading full specs, expert reviews and user reviews. Once a consumer has narrowed down to the product or a few products they like, they can use the Deals and Prices feature and find which stores sell the product at the best prices.

The end result is we quickly educate consumers on what to expect in a product category and guide them through the shopping process to help find the right product to buy whether they want to purchase online or visit a brick and mortar retailer. Benefits to the consumer:

• Instantly learn what to expect for any consumer electronics product category.
• Receive objective advice on products to buy that match their needs.
• Save time and effort as Retrevo does the research legwork for them.
• Quickly understand the main points, value and community sentiment on any CE product.

ShoppingVale was created in response to several years of experience working with leading online retailers and analyzing cross-channel consumer behavior.

Consumers generally start by conducting research; reading reviews, buyer guides, specialized websites among other resources. ShoppingVale allows consumers to conduct this research in the manner they prefer. Our search service provides unbiased, unfiltered access to all available information from the top respected resources.

This unfettered access gives the consumer information that is typically unavailable at comparison sites, such as photographs, Video demos, multi-media product tours and other informative product information.

Once a consumer has an idea of the product they are interested in, ShoppingVale provides easy access to the top retailers for real-time information on price and availability.

Unfortunately other shopping engines like Retrevo, Nextag, _Shopping.com_ <http://Shopping.com> provide information that is filtered and pre-packaged. While this presentation may at first look like an excellent way to compare retailers, the information missing is critical for making an informed decision. Let me tell you a personal story that helped me to kick start ShoppingVale. A while back I was looking for a camcorder and I went to a typical shopping comparison engine to compare prices. At first it appeared that several relatively unknown retailers were selling the camcorder $50 cheaper than a brand-name retailer like Amazon. After exiting the comparison site and going directly to each retailer, I discovered to my disappointment that it wasn’t an apples-to-apples comparison that I was originally led to believe. The non-brand name retailers were only offering a bare-bones camcorder; essentials like the battery and cables were being sold separately. In the end, the smaller retailers were more expensive than Amazon, with a more strict return policy.

ShoppingVale addresses this problem by allowing the consumer to see all the details directly, so they are not being led to believe that all offerings are equal. We give consumers unfiltered access to compare, side by side, each retailer. For example, for electronics we provide one-click access to Amazon, Best Buy, Circuit City, Wal-Mart, Target, _Buy.com_ <http://Buy.com>, Dell, Costco, eBay among others.

You can also get the money saving coupons at ShoppingVale, just type in the Product name in our “Looking for Coupons” section and start saving money.

Give it a try, just type in “Sharp lcd hdtv” in ShoppingVale and Retrevo you will see the difference. I will let you be the judge.

2. How do you plan to drive users to your site (how will they find you)?

Because we cover the entire lifecycle of consumer electronics and not just shopping we have relevant content that also helps consumers USE the products they buy or find support. Retrevo primarily focuses on SEO and leverages this content. We will also in the near future include advertising but we’ve been very pleased with our SEO and WoM traffic growth so far this year – especially after our recent launch of the Retrevo Product Advisor.

We are advertising online using adwords from Google, Yahoo & Microsoft. We will be advertising on Facebook and MySpace shortly as well. Also, by consistently providing the best results and experience possible. Customization options further enhance the user’s experience. If we do this, shoppers will find out from referrals of friends, colleagues, etc

3. Within the Vertical of Shopping search engines, what features are unique to your search engine?

a) Real-Time product value assessment – Retrevo is the first and only company to assign an algorithmically derived value to each product in a given category.

b) Real-Time community sentiment assessment – Retrevo is the first and only company to aggregate the total community sentiment from both expert reviews and user reviews into a single sentiment rating.

c) Real-time product range assessment – Retrevo is the first and only company that dynamically assesses the range of a product in a given category.

These key features are possible through Retrevo TrevolysisTM  

The basis of TrevolysisTM is the analysis of all the feature values, prices and sentiments of all products in a given category.  It is based on years of research in pattern recognition combining advanced methods in multivariate Bayesian decision theory, supervised machine learning and mark-to-model valuation techniques.  We first determine the price-feature position of each product by analyzing hundreds of thousands of product features (e.g., viewfinder type for a digital camera) and current prices.  The result of this analysis is a crisp visual presentation and/or textual summarization of a product on a product profile or a category map along price-feature axis.  The distribution of all normalized product feature values is further analyzed to identify clusters of products with common features forming the basis for the Product Class summary. 

We then determine the fair value of each product based on its feature set and our proprietary mark-to-model valuation technique.  A Value Rating is computed for each product that reflects the deviation of current price of that product from its fair value.  Since the market conditions change on a daily basis and new products with new features are introduced frequently, a product’s fair value and Value Rating assessment also changes constantly.  This analysis is completely algorithmic and automated.  It aims to provide a holistic and objective fact-based product evaluation.  The time when the latest analysis was performed is displayed along with the summary.  Users can therefore always get the real-time value assessment of a product.

While the fact-based summary provides a very objective assessment of products based on current market conditions, qualitative information associated with the brand and user/expert opinions play a very important role in users’ buying decisions.  We scour the web for expert and user opinions for a given product and analyze them for sentiment for that product.  A single Community Sentiment Rating is computed for a product based on a weighted combination of the expert and user opinions for that product.  The weighting is computed using a set of proprietary and automated mathematical formulae that not only weights each opinion but also weights the domain of the web site containing the review based on the variation of all (and category-specific) product ratings found associated with that domain.  Our analysis is based on over a million expert and user opinions on the web.  The Sentiment Rating for a product is displayed along with the total number of user and expert opinions that it was computed from.

TrevolysisTM provides the industry’s first comprehensive yet simple to understand summary of a product’s facts and sentiments.  It is the first of its kind presentation of fact-based Value Rating that combined with a qualitative Community Sentiment Rating provides a powerful product assessment tool for shopping.

Consumers get direct, immediate and unbiased access to /all/ the information. This information is real-time so it’s always up to date. Our results are not based on a commission from a particular retailer. We do not filter, based on our personal opinion, the results.

4. What is your relationship, if any, to national brands, retail stores (like BestBuy) or local stores?

Although many retailers will appear in our search results for stores and prices we maintain no direct relationships with any retailers at this time.

To maintain our unbiased approach, we do not partner or any way solicit money from the retailers.

5. What is your relationship, if any, with other alternative search engines?  Any partnerships?

Retrevo does not currently have relationships with any of the alternative search engines. 

We are kick-starting the process of reaching out to alternative search engines. We recognize our unique service provides a great value to the consumer regardless of the venue.

6.  What’s one compliment that you could give your debate partner as we end the debate?

They have aggregated some top retailers and made it easy for me to compare different stores.

There is a lot of visual appeal to the site design they implemented.

Thanks Robb and Syed!  Readers, let them know if you have a question or comment.

 One of Zuula’s key advantages is that it does not force its users to trust either a new web index or a proprietary way of combining the results from numerous different search engines.  Instead, Zuula allows its users to continue relying on their favorite search engines, while also gaining quick access to results from other search engines, when they’re needed.  So, no Zuula does not have its own index.  Instead, it displays both the organic search results and, when available, the advertising of other search engines.  Results are displayed in a consistent manner across the different ngines, and there is always a clear distinction between “organic” results and advertising.

We at Quintura do build our own web index. As compared to a traditional web index, the Quintura web index is based on contextual relationships between words and phrases. We believe that any search engine has to have its own web index in order to create a substantial shareholder value and make it sustainable.

2.  Zuula uses “Tabbed” metasearch, and Quintura has a “Tagged” cloud – do you feel that these each have their merits, and if so, what are they?

 Both approaches definitely have their merits.  Indeed, they are complementary in many ways.  Let me explain.  For many people, Zuula (or a more traditional search engine) is what they’ll want to use for most of their searching.  For the majority of searches, the goal is to get the one or two links that you’re looking for, and to get them fast.  Zuula is great for those kinds of searches.

Quintura is complementary to Zuula and other services, then, in the sense that it is useful in those cases where the user isn’t quite sure how to find the information they’re looking for — where the user doesn’t quite know what keywords or search terms to use.  For those situations, Quintura may help the user identify concepts related to their initial search terms.  Using the concepts uncovered by Quintura, the user may eventually get to the information they’re searching for — using Quintura, or perhaps going back to Zuula and using it.

To be completely honest, though, I’d have to admit that Zuula and Quintura are competitive in addition to being complementary.  They are competitive in the sense that they both are useful for difficult searches.  Zuula makes difficult searches easier by facilitating access to results from many different search engines.  Quintura makes difficult searches easier by helping its users find related concepts with which to improve and narrow their searches.   Yet I wouldn’t overemphasize this competitive aspect of the two services.  It exists, but it shouldn’t overshadow the extent to which they can be used as complements to one another.

Today’s search engines require people to know how to query and then to mechanically sort through information to find what they want (or not). Quintura turns searching into finding. Quintura offers users a unique and simplified experience. With a single word, Quintura helps users refine their search, exposing all kinds of information in a single view. With a Quintura tag cloud users control their search process. Even if they don’t know what they are looking for – Quintura helps people explore new possibilities and find information.

3. For Boris – how is Zuula different from other similar metasearch engines? And for Yakov, how does Quintura differ from other tag clouds?

 Zuula is a very different metasearch engine.  True, like all metasearch engines, Zuula makes it possible to view results derived from multiple source search engines.  Most metasearch engines, however, combine search results from multiple search engines, often intermingling organic results and advertising. 

Zuula, in contrast, keeps the results from different engines separate from one another.  It also clearly separates organic results and advertising.  Zuula adopts this approach because its goal is to make it possible for its users to rely on their preferred search engines for most of their searching, while also having quick access to results from other search engines when they’re needed.

With a Quintura tag cloud, users can get to the information they need more dynamically and intuitively. They can get to deeper links quickly, not only getting to the information they seek – but to the hidden information they didn’t even know could be found. Quintura allows users to control the search process rather than the search process or technology controlling the user.

4. Will an “Alternative” search engine ever reach 5% of search market share?  If so, will it be you?

 I’m certain that an “Alternative” search engine will one day leap the 5% market share hurdle.  I’m not optimistic, however, that this will take place very soon.  I think the major search engines have developed formidable leadership in many different areas critical for search success.  This leadership makes it difficult for an “alt” to gain noticeable market share in the near future.

Will Zuula achieve a 5% share of the search market?  All of us on the Zuula team certainly hope so, and we’re working hard to make it happen.  But we’re also modest enough to recognize that it’s likely to be a long time until we even come remotely near that target.

It should reach a much larger market share. Our investors Mangrove Capital Partners once said “The next Google will come out of Eastern Europe” and we share that vision with them.

5. What is your relationship, if any, with other search engines?
How do feel about partnerships?

 We’ve been very fortunate at Zuula in regard to our relationships with other search engines.  I believe this is due to some very conscious decisions we made when we launched Zuula. The first decision was to make Zuula freely accessible to any user, and to always keep our users in mind as we develop Zuula further.

The second decision was to never, ever, try to make even a cent of revenue from Zuula as we continue to evolve the site’s initial features and functionality.

The third decision was to show deep respect for our source search engines by fully maintaining the integrity of their search results and their advertising.  Not surprisingly, after some initial apprehension in the community about our goals and policies, I think it became clear that we can be a valuable partner and an ideal showcase for the impressive variety the search industry has to offer. So we have been very open to partnerships, and this will undoubtedly continue to be the case going forward.

We currently make use of web indexes of other search engines such as Yahoo! and Yandex as well as using our own index on Quintura Kidsand Quintura for site search. For example, we use an index of Blinkx video search engine to find videos since Blinkx currently has one of the largest web indexes of videos. In fact, Quintura could be implemented as a visualization layer on top of any search index. That is why we are open to any mutually beneficial partnership. However, our goal is to build a standalone business and beat Google by providing a superior search experience, offering a new site search model for web publishers, and delivering much better search results to users.

Thank you, Boris and Yakov.  Readers, if you have a question for Zuula or Quintura, please leave a comment and we’ll ask them to check back as time allows.

Every Tuesday night on AltSearchEngines, we invite two vertical search engines to discuss the similarities and differences with their projects.  Tonight is one of the most interesting ones that we have ever had - the exotic (to me) world of Arabic / English search engines featuring two very respected search engines: Onkosh and Tayait.


1) For all of our readers who know English but not Arabic, please summarize the challenges that you have faced in building an Arabic / English search engine and how you solved them.

In order to build a search engine, you must first give your system the ability to understand the relationship between various different factors – specifically, the relationships between individual words and the overall structure of the language.

A computer’s ability to understand and process a language is based on a Natural Language Processing (NLP) – and while many languages have been comprehensively understood through NLP technology, Arabic is one of the few major languages left on earth in which major headway is still being made till today.

It is the nature and complexity within the actual language itself that has caused this delay in its development. There are two major hurdles that need to be surpassed when it comes to the application of NLP technology to Arabic:

Both of these realities about the Arabic language create a level of intricacy that as humans comfortable with the language, we have no problem understanding – but when it must be reduced to a rule-based system creates a level of complexity that is very difficult to process.

In order to solve these problems we partnered with an international company that has dedicated part of its R & D to Arabic language processing for the last 15 years, and brought in several of our own NLP specialists to develop our own NLP module, tama (taya Arabic Morphological Analyzer). Using tama we can choose to search all the inflections, derivatives, and all possible synonyms of the word – this alongside the ability to search for a term in English and return all the Arabic results that are related to that term.

The main challenge lies in the fact that the Arabic language is much more complex than the Romanized-based languages.

The Arabic language has a complex script and rules. Add to that, there are invisible characters (called diacritics or ‘tash.keel’) which can alter the way the word is pronounced, and can have a completely different meaning and root—compared to English, a quite ‘straight forward’ language.

Thus, it would be hard to judge relevancy of Arabic search results. In Onkosh, these issues are handled in a smart way that can practically maintain accuracy, and most importantly maintain search time/performance to much less than a second for 92% of the queries, even with high load of concurrent queries.

It is worth mentioning the fact that the ‘giant’ SE’s are mostly treating Arabic blindly (i.e. doing exact match). This does not help the user seeking relevant Arabic information, rather just exact-match results.

Another main challenge is auto-identifying the Arabic-related portion of the web (index coverage). Onkosh tries as much as possible to include not only the Arabic-language pages, but also the ‘Arabic-related’ content in other languages (especially English and French). Building a smart and Arabic-oriented crawler was in itself very challenging.

2) We (in the U.S.) hear a lot about the U.S. and Chinese markets (Baidu, etc.) Where would you place the Arabic market for Search in a global context? How large is it (how many users)? Is it growing, at what rate, etc.?

Well the easiest way to look at the Arabic market and compare it to other language specific markets around the world is by looking at the total number of Internet users that are currently online and use their historical growth rates to extrapolate how this number will continue to grow.

Historically the Chinese market has been considered one of the largest developing markets in the world – and within the last seven years (from the years 2000 – 2007) they have seen an approximate 720% increase in their total number of internet users – going up from 22.5 to 162 million users.  Japan – considered another developing market considered to have massive potential, has had an increase of 185% – going up from 47 to 87.5 million users online.

The interesting thing about the Arabic market – is that it cannot be divided into a single specific country – as it is a language spoken in varying degrees throughout an entire region of countries (including not only the Middle East – but North Africa as well). The North African region (specifically Morocco, Algeria, Egypt, and Libya) has seen a growth rate of almost 2500% in the last seven years in the total number of internet users.

The Middle East (including Jordan, Kuwait, Lebanon, Saudi Arabia, Syria, and the UAE) has seen another 700% increase. This comes out to an estimated 22 million users online today. Though this total number may not compare to that of China or Japan currently – this is a market with an incredible potential and we only expect the adoption and penetration rates of Internet technology to increase in the future.

[Same question]  A lake, small by nature, can be nothing within a huge ocean. This is the case for the Arabic web as part of the global Internet.

We can safely claim a few estimations based on a pseudo-scientific observation and analysis:

First: the Arabic web is currently somewhere in the size of 200-300 million pages only.

Second: the growth rate is very aggressive.

Third: a big portion of the old Arabic web is not SEO-friendly – this getting fixed as sites are added or revamped, since now SEM started to get the webmasters attention in the Middle East and North Africa arena (MENA), where our target audience primarily relies, and of course we target all the Arabs and Arab-speaking users around the globe mostly resident in the U.S., Great Britain, and Canada.

Referring to the Internet statistics website, at the time of writing this (Nov. 18, 2007), we have these growth rates in Internet penetration. The below analysis cohesively indicates parallel growth in the ‘related’ content over the years 2000-2007 (Please compare to total growth of the world which is 244.7%):

2647% growth in North Africa (stats calculated based on the top six Arab African countries: Egypt, Algeria, Morocco, Sudan, Tunisia, and Libya – Excel sheet attached).

Internet Usage Statistics for Africa

920% growth in Middle East: although the population is about 2.9%, the Internet penetration is growing much faster than the rest of the world. The Middle East is not limited to the Arab countries, but the general indicator does the job.

3) You both have the keyboard icon near your search box, could you explain how it is used, and also, for someone like me, can you explain the term “Bel-3araby ” to a non-Arabic user!

Here in Egypt, as in the rest of the Arabic speaking world, when you buy a keyboard, laptop, cell phone, etc – alongside the normal QWERTY keyboard we also have the Arabic alphabet printed (this is the extent to which the Arabic language is engrained in the community – the majority of SMS’s are even sent in Arabic on specially manufactured phones with Arabic letters printed on their keypads).

That being so, Tayait is not designed to be used only by users living within the Arabic world. We realize that there are a huge number of Arabic speakers throughout the globe – who would love to have access to Internet content in their native language – yet who may not have an Arabic keyboard. We, therefore, offer our online Arabic keyboard as a means through which users can quickly and effectively input search terms of their choice – whether they have an Arabic keyboard or not.

We realize though that sometimes using an online keyboard can be cumbersome for entering search terms – especially for power searchers who initiate many different queries at the same time to try and get the best result – this is why we have offered our Cross Language Functionality – offering our users the ability to use a normal English QWERTY keyboard and input the desired search term in plain English, while tama will take care of returning all the relevant Arabic search results to this English query.

[Same question] The keyboard usage is quiet simple. Once you click the icon, your Arabic queries become a few clicks away, even if your computer does not support Arabic at all. This even helps users who have difficulty or slowness in Arabic typing. Additionally, it is ideal for the Arabs living in the U.S. and other places where it is very rare to find Arabic keyboards. 

As for the feature “Bel-3araby”, this is first an Arabic word pronounced
as ‘bel-a’araby’ and means ‘in Arabic’. The feature is patent-pending,
and the term “Bel-3araby” itself is copyrighted to Onkosh. On that note,
I am very proud to say that I am a co-inventor, among five, of the
patent.

This feature enables you to use your Latin-based keyboard to write
Arabic words the way they are phonetically uttered using the Roman
characters and numerals that became very popular in people’s chats or
mobile messaging. In short, Bel-3araby is a transliteration service
from Romanized alpha-numerical input to Arabic output. It is an
intelligent service employing lots of careful heuristics and AI
techniques tailored from ground up to understand the Arabic user needs
(You may refer to this previous post.)

Many attempts are now in action to imitate “Bel-3araby”, after its
importance was recognized at Onkosh.

4) Are there positive things that you see in the other search engine in this debate? Are you competing for exactly the same users, or are there some differences in either a) Your objectives or b) Your approaches, that you could share -as far as you understand your debate partner?

The fact that there are other Arabic search engines out there in and of itself is a positive thing. We believe that Arabic speakers have been held back long enough from being able to effortlessly search the Internet without having to learn a second language – and in that pursuit its incredibly beneficial for all parties to have a variety of companies and people trying out different things in order to provide the best quality search results for Arabic Internet users all around the world. Though the specifics of Onkosh’s objectives are privy only to them, I think we both would agree that the Arabic Internet has incredible potential – if given the infrastructure to thrive. Offering search in Arabic is one of the most critical parts of that infrastructure – but there is much more to come.

We differentiate ourselves and our search results by not only using excellent search technology- but at the same time we have a team of individuals who make the effort of identifying the best quality Arabic websites for the most common search terms to be crawled – this in the hope to provide our users with the highest quality content on the Arabic Internet today. This means that we actively ensure that the most active blogs, news, Wikipedia, and a whole host of Arabic websites are always crawled and indexed – and we continue to add and develop our database daily using the best content we can find.

Yes definitely. They are doing an excellent job in integrating with Exalead, which I find a very good engine indeed. Tayait also have the Arabic synonym search, which is not yet public in our release. Their product Tama has been there for long indicating good performance and reliability.  Our audience overlaps for sure. I am not sure about their preferred segment. Since the Internet has no boundaries, Onkosh defines its audience as all those who use, understand, and/or are interested in the Arabic-related content around the globe.

5) I find both of your projects very impressive; are you the two dominant Arabic / English search engines, or are there others, perhaps less well known ones, that we should also know about that are also good?

Tayait and Onkosh have been in the news quite recently because we have both come out at around the same time in full force. But we haven’t come from a completely nonexistent industry – there are other companies that have been offering Arabic search for a while now, these firms include, but are not limited to:

Araby.com, Arabo.com, Ayna.com, Ajeeb.com, and 4arabs.com

Once again – we think it’s great that there are other like-minded individuals working to provide better services to the online Arabic speaking community.  

Where do you hope to be two years from now?

In the next two years we obviously plan on devoting considerable efforts towards constantly improving our results – as search is our no 1 priority. But it doesn’t stop there – we want to provide Arabic Internet users the same range and quality of services available on the English Internet and in the rest of the world. We know it’s a considerable goal – but it’s something we believe in and are willing to work towards.

There are attempts for building an Arabic search engine Two could succeed to build a good audience: araby.com and ayna.com. We are aware of some other projects that were announced but not yet released like Sawafi, whose latest news said it will be renamed and launched ‘soon.’ 

Expectation for 2010: Two years from now seems a long time span in the fast-moving SE industry and science. What I can safely promise your respectable readers, is that Onkosh will be aggressively enhancing its services over the coming few months. We aim to be the number one local search engine, and to be the most reliable engine for the Arabic-interested user in general. We are very optimistic, and we hope we can help build better Arabic web.

Onkosh has a mission to help the Arabic-speaking user to start sharing and using the Arabic language in search. We are comprehensive in our services, not only depending on the basic form of web search. Onkosh offers other distinguished search flavors including, but not limited to: news, blogs, forums, and files. Not to forget, Onkosh also has a family filter for safe search, in addition to Onkosh.mobi that brings the Arabic web to your handheld device. At Onkosh, we are cordially happy to see others recognize Onkosh as a ‘role model’ in the Arabic search. We believe we did a good job, and we have received a lot of positive feedback that keeps us motivated to even challenge ourselves and work around the clock on more quality features, and we will continue to raise the bar!

AltSearchEngines:  We owe a great debt of thanks to Hany at Onkosh and Noha at Tayait for all of the time and effort that they donated for this debate. If you found it useful, I hope you will print it or email it for anyone else that you think might benefit from this detailed discussion of Arabic search engines. [but please link back to this post]

Of course, I also encourage you to try both of them, Onkosh and Tayait, today, to see their great features for yourselves. If you have a question or comment for Onkosh or Tayait, please leave a comment and we will ask them to check back and respond as they have time.

:   

 

Search Results: Answers.com and  SenseBot.

MetaSearch:  Intelways, GoshMe, and Srchr.


Visualization: KoolTorch and searchCrystal

MP3 Search: MP3Realm and SkreemR.

Media Search: PodNova and Blinkx and EveryZing




Game Search: Wazap! and GameSkoot  

Social Search: Searchles and Wikia

Video Search: Dabble, and ClipBlast!

Health Search: GoPubMed and SearchMedica


People Search: Wink and yoName

Job Search: Recruit.net and SimplyHired.

Peer-to-Peer Search: ATLAS and FAROO 

Ticket Search: tickex and NinjaTickets

Would you like to schedule a debate?
Just email me at: Charles@ReadWriteWeb.com

Ticketmaster is one of many Primary ticket outlets.  They sell allocations of tickets directly from the event promoters to the public. So this means that once Ticketmaster has sold out it doesn’t necessarily mean that the event has sold out.  Other Primary sources may have tickets available still as well as the secondary market. Ticketmaster also deals with the printing and delivery of the tickets.

What TickEx does is take an objective view of the entire ticket market.  We provide ticket data from primary and secondary ticket providers so the consumer sees a completely transparent marketplace. We give the consumer a comparison shopping/vertical search engine for live event tickets allowing them to see prices and availability from the numerous vendors all in one simple and fun to use search.

We simply show the consumer who has what and for how much in the world of tickets.

Ticketmaster has direct contracts with event promoters and venues to sell box office tickets online. Ticketmaster, however, can quickly sell out of tickets, and does not provide a complete listing of primary tickets for all events. That’s where Ninja Tickets comes in. Ninja Tickets indexes and compares tickets from multiple secondary sources (i.e. resales) that rarely sell out of tickets as well as from multiple primary sources. Our aim is to categorize nearly every ticketed event as well as provide a source to compare and find the best prices on popular events.

2.  How do you keep your ticket results up to date considering the short “shelf” life of tickets?”

We up date our ticket records multiple times a day to ensure the customer receives the most up to date information on pricing and availability.

A huge problem with comparing and indexing event tickets is their short shelf life. A hot ticket or a high value ticket will be bought within minutes of being posted. For comparison shopping, Ninja Ticket’s Live Results™ is essential to enabling shoppers to find the best deals. At Ninja Tickets we have industry exclusive technology which allows us to deliver Live Results™ at the time of search across all stores that we index.

3. Considering the amount of ticket results, how does your site sort tickets?

Currently the number of tickets in our index is astounding, this is partly because our high level of coverage in all markets in the US but also because we cover the UK and are expanding throughout Europe as well.

To get through the amazing selection of tickets in our database we have introduced an industry leading set of sorting tools to help you find the best ticket for you.

All of our columns in the result sets are sortable.  We have a price filter that can narrow your results from both ends.  There’s a date filter, a city filter and a venue filter that allow you to see multiple cities on multiple dates and compare prices in the different cities.

Usability is extremely important to Ninja Tickets. For popular events, 5,000 tickets may be indexed making presentation and sorting of these tickets essential to a user’s ability to effectively digest such a vast amount of information. Ninja Tickets offers sorting by quantity, price, section, and value.

Our “Price Rating” feature sorts tickets by the highest value; it’s an extremely powerful and easy tool to use. This tool is extremely valuable because comparison shopping for tickets isn’t the same as comparing handbags or cars as there are so many variables in terms of ticket value, most notably where the ticketed seat is within the venue.

4.  Do you actually sell tickets to events?  If not, what is your business model?

The beauty of our business is that we never actually touch the tickets or deal with any fulfillment.  We are what we like to call a ’super affiliate’.  It is our business to provide a great service to the consumer by making searching for tickets quick, painless and relieving because they can go away feeling like they got the best deal on a ticket available.

NinjaTickets.com is neither a direct ticket seller nor a reseller. Ninja Tickets searches for tickets from Internet ticketing stores and displays this information in a useful array. Ninja Tickets is intended to be a “one-stop” resource for locating the best value in tickets. Our main objective is to provide an unbiased, information-rich site that will attract repeat users.

5.  Are there ways in which a Ticket Search engine can have a mutually beneficial relationship with another, more general, Alternative Search Engine?

I think there are always ways that alternative search engines can benefit each other.  There are many instances that I can see TickEx partnering with other search engines out there and them being beneficial to both parties involved.

Yes, we can have a mutually beneficial relationship, that’s already in the works.

Editor’s note: Will you share it with us when you can?

6.    Where would you like to be in one year – at the very end of 2008?

By the end of 2008, I see TickEx rapidly growing as the place to go to find tickets in the eye of the consumer.  I see our service becoming the benchmark for vertical search plays in terms of quality of results, impartiality and cutting edge design. 

By December 2008, NinjaTickets will index many more sources and expand its event data. The goal of this development is to provide even better functionality and usability for searchers who want to go to one source to find all their event tickets at the best price.

I want to thank Dan and Cliff for their amiability!  If you have a question for them, please leave a comment and I’ll ask them to take a look.

FAROO: Our users provide infrastructure, and ranking, and we provide technology, so in fact we are building our search engine together.  Therefore we decided that our users should also participate in the revenues.  Not some minor percentage, we are sharing revenues of up to fifty percent with our users.  They may donate their share for charity organizations, joining their forces not only for search, but also for helping other people.

Of course users also benefit from the collectively generated ranking and privacy protection. Currently we are about to define an API for FAROO’s distributed database.  That would allow everybody to use the distributed index, the collected information and ranking, both commercially and non-commercially, in mash-ups, with their own interfaces…

Probably there will be some contribution/usage-ratio, to keep the p2p-principle working.

ATLAS: Atlas is primarily for search implementers and services, not really end users. The model supports both free, attribution-based, and paid relationships, every entity must choose how they want to provide value into the network and what kind of reward they need for doing so. 

 7) Privacy: How do you protect the privacy of your users?

FAROO: FAROO does not collect any search log files. All search queries and the distributed index are encrypted.  Neither the other peers nor any intermediate party may observe searches or visited pages.

Due to the fully distributed architecture, FAROO is in fact working as a p2p anonymizer for searching, ranking and crawling.  No personal information is leaving the computer at any time. Even personalization is done client side.

We are giving back search privacy and censor resistance to the user, something what is more and more fading away with current search engines. 

ATLAS: There is no session data / cookies, IP addresses, or any user information whatsoever supported by Atlas.

Spam: How do you deal with search engine spam or SEO manipulation?

FAROO: With our attention-based ranking, SEOs efforts are not deciding the rank anymore, but the community of users itself.  Results which are of no interest to the users automatically lose rank and disappear from search results. With several statistical measures FAROO prevents bogus peer manipulation. 

ATLAS: Through competition, if any entity is injecting spam or being manipulated, competing entities have an opportunity to provide a higher quality.

9) When do you plan on having both a private beta, and a public one?

FAROO: During our presentation at TechCrunch40 September 17th we started our private beta. This is mainly intended to test and improve our distributed architecture.Using a dedicated crawler we are now increasing the number of indexed documents to prevent a “chicken or egg problem”, preparing our public launch later this year. 

ATLAS: Near the end of this year, being open source, they are one and the same .

10) Partners: What, if any, is your relationship with the dozens of “alternative” search engines? Any partnerships past, present or in the future?

FAROO: We are just about to start our search engine, so there are no partnerships with “alternative” search engines yet.  Of course we are always looking at what others do, and some recent achievements of “alternative” search engines in result clustering, natural language search or image recognition are amazing.

On the other hand, with opening our distributed index through an API there will be a lot more options for partnering in one or the other way.  But already today we have a lot of strong partnerships, and a lot more are to come – with each of our users

ATLAS: It’s all open source so partnerships don’t apply, anyone can get involved to help if they want to be part of it.

That concludes our two-part debate on Peer-to-Peer (P2P) Search.

I want to heartily thank our participants, Wolf Garbe of FAROO and Jeremie Miller of Wikia.

If you have any questions or comments, please leave them here.