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KDD
2008
ACM
146views Data Mining» more  KDD 2008»
15 years 10 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
2008
ACM
193views Data Mining» more  KDD 2008»
15 years 10 months ago
A family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances
This work introduces a new family of link-based dissimilarity measures between nodes of a weighted directed graph. This measure, called the randomized shortest-path (RSP) dissimil...
Luh Yen, Marco Saerens, Amin Mantrach, Masashi Shi...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
15 years 10 months ago
Local decomposition for rare class analysis
Given its importance, the problem of predicting rare classes in large-scale multi-labeled data sets has attracted great attentions in the literature. However, the rare-class probl...
Junjie Wu, Hui Xiong, Peng Wu, Jian Chen
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
15 years 10 months ago
Mining optimal decision trees from itemset lattices
We present DL8, an exact algorithm for finding a decision tree that optimizes a ranking function under size, depth, accuracy and leaf constraints. Because the discovery of optimal...
Élisa Fromont, Siegfried Nijssen
KDD
2006
ACM
180views Data Mining» more  KDD 2006»
15 years 10 months ago
Learning the unified kernel machines for classification
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...
Steven C. H. Hoi, Michael R. Lyu, Edward Y. Chang