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FLAIRS
2000
13 years 11 months ago
Graph-Based Hierarchical Conceptual Clustering
Hierarchical conceptual clustering has been proven to be a useful data mining technique. Graph-based representation of structural information has been shown to be successful in kn...
Istvan Jonyer, Lawrence B. Holder, Diane J. Cook
KDD
2007
ACM
148views Data Mining» more  KDD 2007»
14 years 10 months ago
Detecting research topics via the correlation between graphs and texts
In this paper we address the problem of detecting topics in large-scale linked document collections. Recently, topic detection has become a very active area of research due to its...
Yookyung Jo, Carl Lagoze, C. Lee Giles
HAIS
2010
Springer
14 years 3 months ago
Graph-Based Model-Selection Framework for Large Ensembles
The intuition behind ensembles is that different prediciton models compensate each other’s errors if one combines them in an appropriate way. In case of large ensembles a lot of...
Krisztian Buza, Alexandros Nanopoulos, Lars Schmid...
KDD
2005
ACM
160views Data Mining» more  KDD 2005»
14 years 10 months ago
Consistent bipartite graph co-partitioning for star-structured high-order heterogeneous data co-clustering
Heterogeneous data co-clustering has attracted more and more attention in recent years due to its high impact on various applications. While the co-clustering algorithms for two t...
Bin Gao, Tie-Yan Liu, Xin Zheng, QianSheng Cheng, ...
SDM
2010
SIAM
217views Data Mining» more  SDM 2010»
13 years 8 months ago
Collaborative Filtering: Weighted Nonnegative Matrix Factorization Incorporating User and Item Graphs
Collaborative filtering is an important topic in data mining and has been widely used in recommendation system. In this paper, we proposed a unified model for collaborative fil...
Quanquan Gu, Jie Zhou, Chris H. Q. Ding