Comments on: Deep Web Technologies’ Vertical Search for Business Information

By: Melissa Barker

Melissa Barker — Mon, 24 Aug 2009 03:07:15 +0000

Great article! It is worth noting that if you are looking for deep Web tools for finding resources beyond scientific information, you should check out http://www.virtualprivatelibrary.com — which offer over 50 different subject directories and search engines built and updated with proprietary bot technology.

By: rasmus refer

rasmus refer — Wed, 14 Jan 2009 17:28:06 +0000

see also Masterseek business search http://www.masterseek.com
49.876.923 Company profile worldwide

By: Hope Leman

Hope Leman — Wed, 14 Jan 2009 15:13:32 +0000

Thanks to all of the above for an edifying disquisition on arcane matters.

I loooooove all of this about Biznar:

* The ability to sort results by source, title, rank, author, or date
* Alerts which you can receive on a daily, weekly, or monthly basis. The Alerts are delivered via email or via an RSS feed
* Ability to specify specific results to be saved, printed, or emailed
* Automatic clustering so you can “drill down” into search results by topic, author, publication, or date

particularly the ability to sort by date and the email alerts. I have set up such of search engine news and Web 2.0 nes and they work like a dream. I work in a medical library so also love Biznar’s sibling, Mednar.

By: Endre Jofoldi

Endre Jofoldi — Tue, 13 Jan 2009 07:31:20 +0000

No metasearch engine (including Clusty which is also a metasearch engine) is able to do full clustering of results because they dont see the whole source of the page.
In that sense Clusty, Biznar or our PolyMeta search engines are very similar.

By: Chris

Chris — Tue, 13 Jan 2009 06:14:33 +0000

Thanks for this article. I have a question regarding the methods used by DWT to federate results. Usually when viewing federated results, the content sources from the remote data stores are not integrated into one result set. For example, if you are federating the results from say 20 sources, the application will basically need to query the 20 remote sources for which it will receive 20 different result sets. Any idea how is the task of merging the distinct result sets into one result set performed?

My next question is regarding the “clustered information” navigation displayed in the left hand of DWT. Isn’t this more of a faceted navigation rather than cluster navigation. Clustered navigation, as displayed in clusty, creates the navigation hierarchy directly from the unstructured information of the documents. It does this by analyzing the key concepts of the result set. Whereas faceted navigation, creates the hierarchy from structured metadata already residing in the documents. It would seem reasonable that the DWT example would have to be an example of a faceted hierarchy since this is a federated solution? If we are speaking of a strictly federated approach the index does not reside locally and therefore is not amenable to the clustering analysis. Thanks again for the article