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» Approximate data mining in very large relational data
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KDD
2007
ACM
168views Data Mining» more  KDD 2007»
16 years 2 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
KES
2008
Springer
15 years 1 months ago
Classification and Retrieval through Semantic Kernels
Abstract. This work proposes a family of language-independent semantic kernel functions defined for individuals in an ontology. This allows exploiting wellfounded kernel methods fo...
Claudia d'Amato, Nicola Fanizzi, Floriana Esposito
SDM
2009
SIAM
129views Data Mining» more  SDM 2009»
15 years 11 months ago
Multi-topic Based Query-Oriented Summarization.
Query-oriented summarization aims at extracting an informative summary from a document collection for a given query. It is very useful to help users grasp the main information rel...
Dewei Chen, Jie Tang, Limin Yao
129
Voted
EDBT
2006
ACM
122views Database» more  EDBT 2006»
16 years 2 months ago
TQuEST: Threshold Query Execution for Large Sets of Time Series
Effective and efficient data mining in time series databases is essential in many application domains as for instance in financial analysis, medicine, meteorology, and environmenta...
Johannes Aßfalg, Hans-Peter Kriegel, Peer Kr...
117
Voted
SDM
2009
SIAM
140views Data Mining» more  SDM 2009»
15 years 11 months ago
Straightforward Feature Selection for Scalable Latent Semantic Indexing.
Latent Semantic Indexing (LSI) has been validated to be effective on many small scale text collections. However, little evidence has shown its effectiveness on unsampled large sca...
Jun Yan, Shuicheng Yan, Ning Liu, Zheng Chen