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» Insights from Network Structure for Text Mining
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PREMI
2007
Springer
15 years 3 months ago
Discovery of Process Models from Data and Domain Knowledge: A Rough-Granular Approach
The rapid expansion of the Internet has resulted not only in the ever-growing amount of data stored therein, but also in the burgeoning complexity of the concepts and phenomena per...
Andrzej Skowron
77
Voted
IADIS
2004
14 years 11 months ago
Relevance feedback using semantic association between indexing terms in large free text corpuses
Relevance feedback has been considered as a means of incorporating learning into information retrieval systems for quite sometime now. This paper discusses the research results of...
Shahzad Khan, Kenan Azam
ICDM
2009
IEEE
125views Data Mining» more  ICDM 2009»
15 years 4 months ago
A Fully Automated Method for Discovering Community Structures in High Dimensional Data
—Identifying modules, or natural communities, in large complex networks is fundamental in many fields, including social sciences, biological sciences and engineering. Recently s...
Jianhua Ruan
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
15 years 10 months ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
KDD
2007
ACM
168views Data Mining» more  KDD 2007»
15 years 10 months ago
Finding tribes: identifying close-knit individuals from employment patterns
We present a family of algorithms to uncover tribes--groups of individuals who share unusual sequences of affiliations. While much work inferring community structure describes lar...
Lisa Friedland, David Jensen