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KDD
2009
ACM
229views Data Mining» more  KDD 2009»
16 years 7 months ago
Relational learning via latent social dimensions
Social media such as blogs, Facebook, Flickr, etc., presents data in a network format rather than classical IID distribution. To address the interdependency among data instances, ...
Lei Tang, Huan Liu
KDD
2008
ACM
119views Data Mining» more  KDD 2008»
16 years 7 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
SIGMOD
2004
ACM
140views Database» more  SIGMOD 2004»
16 years 7 months ago
Incremental and Effective Data Summarization for Dynamic Hierarchical Clustering
Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
Corrine Cheng, Jörg Sander, Samer Nassar
AIRWEB
2007
Springer
16 years 1 months ago
Computing Trusted Authority Scores in Peer-to-Peer Web Search Networks
Peer-to-peer (P2P) networks have received great attention for sharing and searching information in large user communities. The open and anonymous nature of P2P networks is one of ...
Josiane Xavier Parreira, Debora Donato, Carlos Cas...
SIGIR
2012
ACM
13 years 9 months ago
TFMAP: optimizing MAP for top-n context-aware recommendation
In this paper, we tackle the problem of top-N context-aware recommendation for implicit feedback scenarios. We frame this challenge as a ranking problem in collaborative filterin...
Yue Shi, Alexandros Karatzoglou, Linas Baltrunas, ...