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» Phenomenal Data Mining: From Data to Phenomena
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SDM
2012
SIAM
281views Data Mining» more  SDM 2012»
13 years 4 months ago
Contextual Collaborative Filtering via Hierarchical Matrix Factorization
Matrix factorization (MF) has been demonstrated to be one of the most competitive techniques for collaborative filtering. However, state-of-the-art MFs do not consider contextual...
ErHeng Zhong, Wei Fan, Qiang Yang
KDD
2007
ACM
149views Data Mining» more  KDD 2007»
16 years 1 months ago
Distributed classification in peer-to-peer networks
This work studies the problem of distributed classification in peer-to-peer (P2P) networks. While there has been a significant amount of work in distributed classification, most o...
Ping Luo, Hui Xiong, Kevin Lü, Zhongzhi Shi
KDD
2007
ACM
165views Data Mining» more  KDD 2007»
16 years 1 months ago
Efficient and effective explanation of change in hierarchical summaries
Dimension attributes in data warehouses are typically hierarchical (e.g., geographic locations in sales data, URLs in Web traffic logs). OLAP tools are used to summarize the measu...
Deepak Agarwal, Dhiman Barman, Dimitrios Gunopulos...
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
16 years 2 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
137
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KDD
2009
ACM
379views Data Mining» more  KDD 2009»
15 years 6 months ago
MetaFac: community discovery via relational hypergraph factorization
This paper aims at discovering community structure in rich media social networks, through analysis of time-varying, multi-relational data. Community structure represents the laten...
Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi B. Konuru...