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147
Voted
KDD
2008
ACM
165views Data Mining» more  KDD 2008»
16 years 3 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...
111
Voted
KDD
2002
ACM
127views Data Mining» more  KDD 2002»
16 years 3 months ago
Mining knowledge-sharing sites for viral marketing
Viral marketing takes advantage of networks of influence among customers to inexpensively achieve large changes in behavior. Our research seeks to put it on a firmer footing by mi...
Matthew Richardson, Pedro Domingos
SIGMOD
2008
ACM
215views Database» more  SIGMOD 2008»
16 years 2 months ago
CSV: visualizing and mining cohesive subgraphs
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...
179
Voted
EUROISI
2008
15 years 4 months ago
Homeland Security Data Mining Using Social Network Analysis
The tragic events of September 11th have caused drastic effects on many aspects of society. Academics in the fields of computational and information science have been called upon ...
Hsinchun Chen
116
Voted
PAKM
1998
15 years 3 months ago
Knowledge Management: A Text Mining Approach
Knowledge Discovery in Databases (KDD), also known as data mining, focuses on the computerized exploration of large amounts of data and on the discovery of interesting patterns wi...
Ronen Feldman, Moshe Fresko, Haym Hirsh, Yonatan A...