Author: Peggy Anne Salz

In-Brief: The collaboration between AltSearchEngines and MSG gets into gear with a look at BooRah, a restaurant search engine that aggregates restaurant review content and buzz to let users search for what they want how they want it. The approach covers the bases to revolutionize how we might find businesses and services on the fly. Thanks to Nagaraju Bandaru, BooRah Co-founder & CTO, for an excellent webinar, as well as an exciting preview of what’s in the pipeline.

At first glance, BooRah may appear to be a straight-forward restaurant search engine. But take a look under the hood and you’ll find a patent-pending system at work that effectively analyzes user-generated content (restaurant reviews, blogs etc…) to pick up on positive and negative sentiment. Hence the name: Boo refers to negative opinion (what people don’t like), and Rah tells us people gave it a thumbs-up – as in Hoorah!

Equipped with this information – which the technology gleans from semantic and structural analysis it performs on every sentence to identify the adjectives, verbs, and nouns that tell us what others really feel – the search engine lets users find restaurants they’re sure to like (based on factors including food, service, and ambience).

Pair this with mobile, as BooRah did just a few weeks ago, and you have a smart service that is location-aware and buzz-sensitive.

The service is in Alpha and will need a few more features before the company can call it a full Beta. Nagaraju tells me he just added directions and will continue to add features. “Basically, anything you can search for at BooRah.com, you can search for using mobile search.”

MOBILE DECISION-MAKING TOOLS: BooRah taps the wisdom of crowds to bubble up relevant answers and recommendations. “When you are looking for a restaurant, you want to do more than eat. You want to know if it’s a hip place where you can gather with friends for a casual meal, or an upscale restaurant that would be a perfect place to take your date. You want to know that without reading lots of reviews. And on mobile, the relevance that we can bring to results is even more critical.” To avoid information overload, BooRah presents 10 mobile search results. The presentation is neat and clean, and leaves room for related advertising – when the time is right.

NUTS & BOLTS: By way of background, BooRah’s semantic smart search system is built from the ground up to let users perform natural language search for specific experiences, moods and sentiments, and personalize the results. A query for “anniversary in Palo Alto, CA” would search for all relevant comments associated with categories such as “romantic”, “upscale”, “trendy”, “Live-music”, “view”, etc… and lets users filter results based on their preferences.

BooRah’s Natural Language Processing (NLP) technology processes vast amounts of plain English text from user-generated content such as user reviews, opinions, and blogs. It extracts specific user sentiments expressed within the content and generates scores, summaries, and customizable search responses relevant to the consumers. Results are ranked first and foremost according to popularity, and BooRah purposely ignores stars and similar vague and subjective forms of user ratings. A wise move since people rarely give out one star or five – it’s always somewhere in the middle. Rather than wade through this – and risk skewing results in favor of hyperactive contributors or users with ulterior motives for giving thumbs-up or thumbs-down – BooRah hones on opinionated reviews that say why a restaurant is good or bad.

Read the entire article on Peggy’s site HERE.

This entry was posted on Tuesday, June 10th, 2008 at 2:54 pm and is filed under Guest Authors, Reviews, Verticals. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.