How to Achieve Better Enterprise Search

 
 
By Yves Schabes  |  Posted 2009-07-14 Email Print this article Print
 
 
 
 
 
 
 


How to achieve better enterprise search

By automatically tagging and categorizing enterprise content, enterprises will realize the naturally occurring, high-quality metadata associated with hyperlinks, and bridge the gap between enterprise and Internet search. In order to achieve better enterprise search, enterprises should do the following three things:

1. Install a system to automate the creation of metadata for existing content and new content as it's added to the server.

2. Categorize information into logical groups based on folksonomies, taxonomies and ontologies.

3. Define, in advance, what you want to understand from the documents and check to see that automated systems coincide with these goals. Perform a systematic human check of your automated search and content management tools at least once per quarter.

The key to managing your company's content quickly and easily is being able to automatically generate metadata. An auto-categorization metadata system, the backbone of a successful content management system (CMS), is a proven solution for better search and retrieval. It not only improves accuracy and efficiency, but also saves time, money and resources. In today's challenging economic climate, it's hard to argue with that.

Dr. Yves Schabes is President of Teragram. Yves co-founded Teragram with Dr. Emmanuel Roche in 1997. Yves has spent the past fifteen years working on issues relating to natural language processing and computer science. Yves is the author, or editor, of more than fifty international scientific publications, including co-editor, with Emmanuel Roche, of Finite-State Language Processing (1997, MIT Press, Cambridge MA). Yves is also an Associate to the Division of Applied Science at Harvard University.

Prior to founding Teragram, Yves was a Senior Scientist at Mitsubishi Electric Research Laboratories in Cambridge, MA. He also held a position as a Research Associate at the University of Pennsylvania. Yves has been a program committee member of many international scientific conferences and journals.

He received a Ph.D in 1990 in Computer Science from University of Pennsylvania and a M.S. in Electrical Engineering from l'Ecole Sup??«rieure D'Electricit??« (France) in 1985. He can be reached at http://www.teragram.com/cgi-bin/contactys.pl.




 
 
 
 
Dr. Yves Schabes is President of Teragram. Yves co-founded Teragram with Dr. Emmanuel Roche in 1997. Yves has spent the past fifteen years working on issues relating to natural language processing and computer science. Yves is the author, or editor, of more than fifty international scientific publications, including coÔÇôeditor, with Emmanuel Roche, of Finite-State Language Processing (1997, MIT Press, Cambridge MA). Yves is also an Associate to the Division of Applied Science at Harvard University. Prior to founding Teragram, Yves was a Senior Scientist at Mitsubishi Electric Research Laboratories in Cambridge, MA. He also held a position as a Research Associate at the University of Pennsylvania. Yves has been a program committee member of many international scientific conferences and journals. He received a Ph.D in 1990 in Computer Science from University of Pennsylvania and a M.S. in Electrical Engineering from lÔÇÖEcole Sup?®rieure D'Electricit?® (France) in 1985. He can be reached at http://www.teragram.com/cgi-bin/contactys.pl.
 
 
 
 
 
 
 

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