Searching for human-like search

Search is the motherload of the Internet today, as has been proven by Google. But it is still clunky and you end up with 149,000,000 results for "ajax" delivered in .05 seconds.

At the Web 2.0 Summit, hakia showed a beta of its "meaning-based" search engine. According to the company, "the basic promise is to bring search results by meaning match - similar to the human brain's cognitive skills - rather than by the mere occurrence (or popularity) of search terms." 

hakia's Query Detection and Extraction (QDEX) uses semantic analysis, dissecting pages into knowledge bits and storing them as gateways to all possible queries. According to the company, QDEX has superior scalability properties because data segments are independent of each other, and hakia's SemanticRank algorithm includes bits of ontological semantics, fuzzy logic, computational linguistics, and mathematics. Whatever 

Powerset CEO and co-founder Barney Pell told that his search engine would make an appearance around May 2007. In his post on natural language search, Pell spells out some of the ideas behind his development effort:

Instead of keywordese or even advanced keywordese (which few people can remember how to use), true natural language queries have linguistic structure. This includes queries where the function words matter, where word order means something, and where relationships that should be explicitly stated easily are stated. Instead of ignoring the function words, a natural language search engine respects their meaning and uses it to give better results. Instead of being a waste of time for a user to add stopwords in a query, each little word added has a profound effect on the search quality. 

Pell also expects that there will be several more entrants entering the natural language search space. Jack Ma, founder and CEO of Alibaba in China, is also applying his resources to making search more human-like, athough he didn't offer my any details when I spoke with him.

Pell's point of view, which is shared by the entire industry attacking the search problem, is that  there is enormous room for fundamental innovation and that the game has only just begun. 

For visual search, Riya's Like.com engine brings a new dimension to finding objects via similarity.

Later today at the Web 2.0 Summit Jim Lanzone of Ask and Steve Berkowitz of Microsoft are going to talk about beating Google at its own game. Stay tuned...