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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
15 years 10 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
KDD
2010
ACM
247views Data Mining» more  KDD 2010»
14 years 11 months ago
Metric forensics: a multi-level approach for mining volatile graphs
Advances in data collection and storage capacity have made it increasingly possible to collect highly volatile graph data for analysis. Existing graph analysis techniques are not ...
Keith Henderson, Tina Eliassi-Rad, Christos Falout...
SDM
2009
SIAM
208views Data Mining» more  SDM 2009»
15 years 6 months ago
Topic Evolution in a Stream of Documents.
Document collections evolve over time, new topics emerge and old ones decline. At the same time, the terminology evolves as well. Much literature is devoted to topic evolution in ...
Alexander Hinneburg, Andrè Gohr, Myra Spili...
JOT
2007
124views more  JOT 2007»
14 years 9 months ago
Displaying Updated Stock Quotes
This paper describes how to extract stock quote data and display it with a dynamic update (using free, but delayed data streams). As a part of the architecture of the program, we ...
Douglas Lyon
ICDM
2006
IEEE
124views Data Mining» more  ICDM 2006»
15 years 3 months ago
Finding "Who Is Talking to Whom" in VoIP Networks via Progressive Stream Clustering
Technologies that use the Internet network to deliver voice communications have the potential to reduce costs and improve access to communications services around the world. Howev...
Olivier Verscheure, Michail Vlachos, Aris Anagnost...