Promise of a Better Search with Hakia
March 9, 2007 by Trent Adams
I found an interesting new (beta launched 2/13/2007) search engine called hakia. From the looks of it, they’re rolling their own solution on semantic-based stuff. Here’s a blurb from their site:
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 new technology is a radical departure from the conventional indexing approach, because indexing has severe limitations to handle full-scale semantic search.
Interestingly, they purposefully call out specific uses in which they believe their solution is particularly well-suited:
hakia’s capabilities will appeal to all Web searchers - especially those engaged in research on knowledge intensive subjects, such as medicine, law, finance, science, and literature.
I hammered on it for a bit, and it does look like it’s got some good feet under it. I’ll try replacing it as my go-to search site for a while and see how it goes (similar to what I did with AltaVista when I found Google in 1997 - never to look back). More on the experiment - if it develops.
I turned up a short counter-point blog post about their approach by Marc Fawzi and ToxicWave:
“We are beginning to see search engines that claim they can semantic-ize arbitrary unstructured “Wild Wild Web” information. Wikipedia pages, constrained to the Wikipedia knowledge management format, may be easier to semantic-ize on the fly. However, at this early stage, a better approach may be to use human-directed crawling that associates the information sources with clearly defined domains/ontologies.”
I like that idea… at least until the machines are smart enough to push aside their masters (as anyone who reads science fiction knows they’ll do eventually).
Related Posts:
- 5/23/2008 - Collaborative Filtering Melodrama
- 5/14/2008 - Portability with Linked Data
- 1/3/2008 - Dose of Reality
- 11/13/2007 - First Use of PowerMouse
- 9/24/2007 - Cross-Media Recommendations a Hit














