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» Mining Very Large Databases
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144
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WSDM
2012
ACM
254views Data Mining» more  WSDM 2012»
13 years 11 months ago
Maximizing product adoption in social networks
One of the key objectives of viral marketing is to identify a small set of users in a social network, who when convinced to adopt a product will influence others in the network l...
Smriti Bhagat, Amit Goyal 0002, Laks V. S. Lakshma...
164
Voted
KDD
2012
ACM
196views Data Mining» more  KDD 2012»
13 years 6 months ago
Chromatic correlation clustering
We study a novel clustering problem in which the pairwise relations between objects are categorical. This problem can be viewed as clustering the vertices of a graph whose edges a...
Francesco Bonchi, Aristides Gionis, Francesco Gull...
146
Voted
KDD
2012
ACM
166views Data Mining» more  KDD 2012»
13 years 6 months ago
Selecting a characteristic set of reviews
Online reviews provide consumers with valuable information that guides their decisions on a variety of fronts: from entertainment and shopping to medical services. Although the pr...
Theodoros Lappas, Mark Crovella, Evimaria Terzi
SIGMOD
2009
ACM
182views Database» more  SIGMOD 2009»
16 years 4 months ago
3-HOP: a high-compression indexing scheme for reachability query
Reachability queries on large directed graphs have attracted much attention recently. The existing work either uses spanning structures, such as chains or trees, to compress the c...
Ruoming Jin, Yang Xiang, Ning Ruan, David Fuhry
ICDM
2008
IEEE
146views Data Mining» more  ICDM 2008»
15 years 10 months ago
Hunting for Coherent Co-clusters in High Dimensional and Noisy Datasets
Clustering problems often involve datasets where only a part of the data is relevant to the problem, e.g., in microarray data analysis only a subset of the genes show cohesive exp...
Meghana Deodhar, Joydeep Ghosh, Gunjan Gupta, Hyuk...