'Natural Language Processing (NLP)' Category
POTW to return next week
I will be returning to writing next week after a great ApacheCon Europe conference last week. My “Advanced Lucene” slides are available at http://www.cnlp.org/presentations/present.asp?show=conference
Next week, I think I am going to start looking into things like event detection, etc. However, I am also considering looking into some non-NLP areas related to data mining, so if [...]Popularity: 3% [?]
Guest Contributor wanted for next 3 weeks
If you have an interest in writing on artificial intelligence, clustering, information retrieval or computer science in general and are interested in reviewing one or more articles over the coming three weeks on this forum, please contact me by leaving a comment on this post. All topics will be subject to my review for appropriateness, [...]
Popularity: 11% [?]
POTW: 4/8/07: “Scatter/Gather: A Cluster-based Approach to Browsing Large Document Collections” by Cutting, et.al
This week’s paper is “Scatter/Gather: A Cluster-based Approach to Browsing Large Document Collections” by Cutting, Karger, Pedersen and Tukey. This is one of Doug Cutting’s older works on clustering, pre Lucene fame.
Popularity: 4% [?]Popularity: 4% [?]
POTW 3/26/07: “Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition” by Osinski, Stefanowski, and Weiss
Finally, a chance to finish up last week’s review on “Lingo” by Osinski, et. al. I first came across Lingo via the Carrot Search and it’s associated Carrot clustering engine. Mr. Weiss also chimes in on the Lucene mailing list from time to time when people ask about clustering Lucene results.
To start, the paper explains [...]Popularity: 5% [?]
POTW 3/26/07: “Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition” by Osinski, Stefanowski, and Weiss
Paper of the Week for March 26 is “Lingo: Search Results Clustering Algorithm Based on Singular Value Decomposition” by Osinski, et. al. Aah, back to matrices…
Popularity: 3% [?]Popularity: 3% [?]

