Welcome to the offices of Dr. Hong Liang Qiao, Founder and CEO of Lexxe, Australia. Dr. Qiao has graciously offered to help us understand semantic search engines.
How can we understand and evaluate a semantic search engine?
Semantic search engines are starting to gain attention, now more than ever. Dr. Riza Berkan, founder and CEO of Hakia gave a very in-depth explanation of semantic search recently, here. Natural Language search technology (or Natural Language Processing; NLP) will have a huge breakthrough, if adequate resources are available. In my view, the advancement of Natural Language search technology depends on a rich set of linguistic data that can be constructed massively. It would be a finite set of linguistic data that can be completed within a few years, just like the decade long Human Genome Project.
Intelligent Search Engines?
If this is eventually done, it would enable search engines to become intelligent enough to understand most of the questions people ask, retrieve more accurate answers, and return more relevant web results than today. A more humanised search interface, more accurate results and more efficient communication between humans and machines will give users a whole new experience that will not be like what it is today. When people test semantic search engines these days, they tend to try them out superficially, often with just 3 or 4 queries. There is nothing wrong with that. However, some could make quite serious conclusions immediately.
Where we are now?
Although everyone is free to do so, it is a bit unfair to semantic search engines, particularly since many are still in the Alpha or Beta stages. Given the current level of linguistic data support and the innovative performance of semantic search engines, one might start to re-think the way he/she sees new technology, hopefully with a more futuristic perspective. Even semantic search could not satisfy everyone’s needs, but there is simply no doubt about this approach for the future of search technology, because queries and information returned by search engines are mostly made up of language. Even video, image, sound, and many other materials are mostly searched via language, although I am aware that some image searches can be done through images alone.
First, let’s take a look at Key Word Search
For Key Word Search, one may perhaps consider the following issues:
1a) Are snippets helpful enough? Can you find what you want without opening new web pages?
1b) In the top ten results, how many snippets are useful and provide the information you want?
1c) If you do need to open the web results (because the snippets couldn’t help you), how many web result pages contain the information you want and in what position of the top ten?
1d) If the semantic search engine provides clusters and if they offer useful information that answers your query and saves you from extra work (e.g. from clicking open the web result links), semantic search engines should score some points here.
1e) Generally speaking, the less effort and time you spend in finding the information, the fewer clicks and reading you have do, the better that search engine is.
Dooniz makes hundreds of affiliations with major websites on the Internet. These websites give Dooniz a commission to bring them customers. When Dooniz refers somebody to one of its affiliated sites, money is redistributed to a list of major foundations around the planet. 
Snooth is a wine search engine, and lately it’s been growing like gangbusters! 
Caronte Web
Federated Search
Highlight Health
MSearchGroove
Ramenos Blog
Reel SEO
Software Abstractions
The Genius Files
The Next Web