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» Clustering Text Data Streams
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SAC
2009
ACM
14 years 2 months ago
Combining statistics and semantics via ensemble model for document clustering
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...
Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan
AINA
2008
IEEE
13 years 9 months ago
A Communication-Efficient Distributed Clustering Algorithm for Sensor Networks
Sensor networks usually generate continuous stream of data over time. Clustering sensor data as a core task of mining sensor data plays an essential role in analytical application...
Amirhosein Taherkordi, Reza Mohammadi, Frank Elias...
LREC
2010
155views Education» more  LREC 2010»
13 years 9 months ago
A Named Entity Labeler for German: Exploiting Wikipedia and Distributional Clusters
Named Entity Recognition is a relatively well-understood NLP task, with many publicly available training resources and software for English. Other languages tend to be underserved...
Grzegorz Chrupala, Dietrich Klakow
CIKM
2003
Springer
14 years 28 days ago
Tracking changes in user interests with a few relevance judgments
Keeping track of changes in user interests from a document stream with a few relevance judgments is not an easy task. To tackle this problem, we propose a novel method that integr...
Dwi H. Widyantoro, Thomas R. Ioerger, John Yen
ICDM
2005
IEEE
188views Data Mining» more  ICDM 2005»
14 years 1 months ago
CLUMP: A Scalable and Robust Framework for Structure Discovery
We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...
Kunal Punera, Joydeep Ghosh