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KDD
2008
ACM
120views Data Mining» more  KDD 2008»
16 years 6 months ago
Entity categorization over large document collections
Extracting entities (such as people, movies) from documents and identifying the categories (such as painter, writer) they belong to enable structured querying and data analysis ov...
Arnd Christian König, Rares Vernica, Venkates...
KDD
2007
ACM
184views Data Mining» more  KDD 2007»
16 years 6 months ago
GraphScope: parameter-free mining of large time-evolving graphs
How can we find communities in dynamic networks of social interactions, such as who calls whom, who emails whom, or who sells to whom? How can we spot discontinuity timepoints in ...
Jimeng Sun, Christos Faloutsos, Spiros Papadimitri...
KDD
2006
ACM
147views Data Mining» more  KDD 2006»
16 years 6 months ago
Summarizing itemset patterns using probabilistic models
In this paper, we propose a novel probabilistic approach to summarize frequent itemset patterns. Such techniques are useful for summarization, post-processing, and end-user interp...
Chao Wang, Srinivasan Parthasarathy
KDD
2003
ACM
156views Data Mining» more  KDD 2003»
16 years 6 months ago
Fast vertical mining using diffsets
A number of vertical mining algorithms have been proposed recently for association mining, which have shown to be very effective and usually outperform horizontal approaches. The ...
Mohammed Javeed Zaki, Karam Gouda
KDD
2002
ACM
166views Data Mining» more  KDD 2002»
16 years 6 months ago
Frequent term-based text clustering
Text clustering methods can be used to structure large sets of text or hypertext documents. The well-known methods of text clustering, however, do not really address the special p...
Florian Beil, Martin Ester, Xiaowei Xu