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» Constellations and the Unsupervised Learning of Graphs
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COLING
2010
13 years 2 months ago
Sentiment Translation through Multi-Edge Graphs
Sentiment analysis systems can benefit from the translation of sentiment information. We present a novel, graph-based approach using SimRank, a well-established graph-theoretic al...
Christian Scheible, Florian Laws, Lukas Michelbach...
MM
2005
ACM
134views Multimedia» more  MM 2005»
14 years 1 months ago
Graph based multi-modality learning
To better understand the content of multimedia, a lot of research efforts have been made on how to learn from multi-modal feature. In this paper, it is studied from a graph point ...
Hanghang Tong, Jingrui He, Mingjing Li, Changshui ...
ICDM
2006
IEEE
152views Data Mining» more  ICDM 2006»
14 years 1 months ago
Application of Graph-based Data Mining to Metabolic Pathways
We present a method for finding biologically meaningful patterns on metabolic pathways using the SUBDUE graph-based relational learning system. A huge amount of biological data t...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
SIGIR
2011
ACM
12 years 10 months ago
Pseudo test collections for learning web search ranking functions
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
14 years 2 months ago
Clustering with Multiple Graphs
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...
Wei Tang, Zhengdong Lu, Inderjit S. Dhillon