Textdigger to launch semantic search engine

By Vivek | January 30th, 2007 at 10:36 am ET         

TextDigger will be launching its semantic search engine at DEMO today. TextDigger is not another one in the series of startups that are launched every now and then claiming Google is pretty bad at what it does and they will make sure that the injustice is stopped. TextDigger does something important which adds gives an interesting dimension to search space- Search engine being able to find similar words in context to the keywords your searched for. And these are not the keywords taken out of thesaurus we are talking about. Take the case when you are search for “hotel with a view”. The keyword has various dimensions to it – View as in “point of view”, View as used in engineering drawing, and more. However what a user is looking for is pointers in the direction of “vista”, “panorama”, “landscape”……, which a user might not recall and needs at that point of time.

When you search at TextDigger for any string, it will come up with all regular search results, and on the top of the page gives you the semantic results that can help you refining your search results. TextDigger will be initially opening up the search engine to a select group of beta testers. Semantic part of the search results will operate in a social search fashion with the users having the ability to edit and add to the semantic search index. In case you are wondering about the how they going about building their search and semantic index - TextDigger has built the semantic search engine ground up, while partnering with Gigablast to deliver the regular search results.

Coming to the short history of TextDigger – based out of San Jose, CA, TextDigger was officially started off early last year by 3 lead CNET engineers. Till date TextDigger has received funding from CNET and several angel investors but haven’t done a VC round of funding. Currently TextDigger has 6 people onboard, with varied background in CS, linguistics, and philosophy which gives it a balanced outlook at how users perceive search to be.

Powerset, and Phrasetrain have been working similar problem with slightly different focus in each case. TextDigger team works a lot around linguistics while other might try to solve them the perspective of grammar.

Links:
TextDigger