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» Clustering Text Data Streams
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SAC
2009
ACM
15 years 6 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
15 years 1 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»
15 years 1 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
15 years 5 months 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»
15 years 5 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