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» Using a Hash-Based Method for Apriori-Based Graph Mining
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PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
13 years 7 months ago
Laplacian Spectrum Learning
Abstract. The eigenspectrum of a graph Laplacian encodes smoothness information over the graph. A natural approach to learning involves transforming the spectrum of a graph Laplaci...
Pannagadatta K. Shivaswamy, Tony Jebara
INCDM
2010
Springer
172views Data Mining» more  INCDM 2010»
13 years 7 months ago
Evaluating the Quality of Clustering Algorithms Using Cluster Path Lengths
Many real world systems can be modeled as networks or graphs. Clustering algorithms that help us to organize and understand these networks are usually referred to as, graph based c...
Faraz Zaidi, Daniel Archambault, Guy Melanç...
KDD
2007
ACM
244views Data Mining» more  KDD 2007»
14 years 9 months ago
A Recommender System Based on Local Random Walks and Spectral Methods
In this paper, we design recommender systems for weblogs based on the link structure among them. We propose algorithms based on refined random walks and spectral methods. First, w...
Zeinab Abbassi, Vahab S. Mirrokni
ICDM
2002
IEEE
173views Data Mining» more  ICDM 2002»
14 years 1 months ago
Mining Genes in DNA Using GeneScout
In this paper, we present a new system, called GeneScout, for predicting gene structures in vertebrate genomic DNA. The system contains specially designed hidden Markov models (HM...
Michael M. Yin, Jason Tsong-Li Wang
KDD
2008
ACM
165views Data Mining» more  KDD 2008»
14 years 9 months ago
Colibri: fast mining of large static and dynamic graphs
Low-rank approximations of the adjacency matrix of a graph are essential in finding patterns (such as communities) and detecting anomalies. Additionally, it is desirable to track ...
Hanghang Tong, Spiros Papadimitriou, Jimeng Sun, P...