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117
Voted
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
16 years 1 months ago
SAIL: summation-based incremental learning for information-theoretic clustering
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
Junjie Wu, Hui Xiong, Jian Chen
127
Voted
KDD
2008
ACM
217views Data Mining» more  KDD 2008»
16 years 1 months ago
Stream prediction using a generative model based on frequent episodes in event sequences
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
Srivatsan Laxman, Vikram Tankasali, Ryen W. White
113
Voted
KDD
2008
ACM
138views Data Mining» more  KDD 2008»
16 years 1 months ago
Quantitative evaluation of approximate frequent pattern mining algorithms
Traditional association mining algorithms use a strict definition of support that requires every item in a frequent itemset to occur in each supporting transaction. In real-life d...
Rohit Gupta, Gang Fang, Blayne Field, Michael Stei...
102
Voted
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 1 months ago
Mobile call graphs: beyond power-law and lognormal distributions
We analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. We examine the distr...
Mukund Seshadri, Sridhar Machiraju, Ashwin Sridhar...
110
Voted
KDD
2008
ACM
146views Data Mining» more  KDD 2008»
16 years 1 months ago
Spotting out emerging artists using geo-aware analysis of P2P query strings
Record label companies would like to identify potential artists as early as possible in their careers, before other companies approach the artists with competing contracts. The va...
Noam Koenigstein, Yuval Shavitt, Tomer Tankel