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KDD
2009
ACM
159views Data Mining» more  KDD 2009»
16 years 2 months ago
Adapting the right measures for K-means clustering
Clustering validation is a long standing challenge in the clustering literature. While many validation measures have been developed for evaluating the performance of clustering al...
Junjie Wu, Hui Xiong, Jian Chen
KDD
2009
ACM
223views Data Mining» more  KDD 2009»
16 years 2 months ago
Collaborative filtering with temporal dynamics
Customer preferences for products are drifting over time. Product perception and popularity are constantly changing as new selection emerges. Similarly, customer inclinations are ...
Yehuda Koren
KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 2 months ago
User grouping behavior in online forums
Online forums represent one type of social media that is particularly rich for studying human behavior in information seeking and diffusing. The way users join communities is a re...
Xiaolin Shi, Jun Zhu, Rui Cai, Lei Zhang
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 1 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
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