I've looked over this sight pretty thoroughly and I still can't tell when the Text Mining capabilities were last updated.
Were they updated for SQL Server 2008 and if so what is the new functionality? Can you please point me to any updated documentation? All I've found so far - after an hour of looking is the "Text Mining Tutorial" which was written back in '05/'06 - (it apparently was uploaded to the site in 2008 but the actual date on the file in the Zip package is 2005)
If I just overlooked it then please accept my apologies now and lets definitely avoid a spam contest.
Do we (I work for Microsoft) have plans to really get serious about Text Mining - to the point were we can compete with the major data mining products? Need to know so that I can make purchasing decisions.
I have also downloaded that tutorial and have found that it is far from complete.
You have other options. Both the book "Data Mining with SQL Server 2008" and "MS SQL Server 2008 Integration Services" have good examples of how to set up Term Extraction /Term Lookup and Fuzzy Grouping / Fuzzy Lookup.
It would be nice to hear more about the functionality SQL Server 2008 compares to other supplyers.
I've been exploring text mining capabilities of 2005 for the last month and would also like to know any enhancements in the 2008 version. As you've stated the tutorial is all I could find as well and it seems incomplete. I also ran into another article from Peter Pyungchul Kim which when combined with that tutorial seemed to help.
One closest improvement (new features) you can find is Semantic search capabilities of SQL SERVER 2012
Text analytics software can help by transposing words and phrases in unstructured data into numerical values which can then be linked with structured data in a database "Deployment" in this context means putting the model into production use, for example: by querying it from a CRM application and using it to provide real-time suggestions. If the decision tree only has one node, it means that no significant splits were found with respect to the column (attribute) you're trying to predict.
Ahsan Kabir Please remember to click Mark as Answer and Vote as Helpful on posts that help you. This can be beneficial to other community members reading the thread. http://www.aktechforum.blogspot.com/