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KDD
2008
ACM
146views Data Mining» more  KDD 2008»
16 years 3 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
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 3 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
139
Voted
KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 3 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
145
Voted
KDD
2005
ACM
153views Data Mining» more  KDD 2005»
16 years 3 months ago
Improving discriminative sequential learning with rare--but--important associations
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
Xuan Hieu Phan, Minh Le Nguyen, Tu Bao Ho, Susumu ...
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
16 years 3 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
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