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» Mining Very Large Databases
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139
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SDM
2010
SIAM
183views Data Mining» more  SDM 2010»
15 years 4 months ago
GraSS: Graph Structure Summarization
Large graph databases are commonly collected and analyzed in numerous domains. For reasons related to either space efficiency or for privacy protection (e.g., in the case of socia...
Kristen LeFevre, Evimaria Terzi
169
Voted
KDD
2012
ACM
242views Data Mining» more  KDD 2012»
13 years 5 months ago
Query-driven discovery of semantically similar substructures in heterogeneous networks
Heterogeneous information networks that contain multiple types of objects and links are ubiquitous in the real world, such as bibliographic networks, cyber-physical networks, and ...
Xiao Yu, Yizhou Sun, Peixiang Zhao, Jiawei Han
128
Voted
KDD
2002
ACM
115views Data Mining» more  KDD 2002»
16 years 3 months ago
Collaborative crawling: mining user experiences for topical resource discovery
The rapid growth of the world wide web had made the problem of topic speci c resource discovery an important one in recent years. In this problem, it is desired to nd web pages wh...
Charu C. Aggarwal
ICTAI
2006
IEEE
15 years 9 months ago
On the Relationships between Clustering and Spatial Co-location Pattern Mining
The goal of spatial co-location pattern mining is to find subsets of spatial features frequently located together in spatial proximity. Example co-location patterns include servi...
Yan Huang, Pusheng Zhang
ECWEB
2004
Springer
179views ECommerce» more  ECWEB 2004»
15 years 8 months ago
Applying Text Mining on Electronic Messages for Competitive Intelligence
This paper presents how text -mining techniques can be used to analyze an enterprise’s external environment searching for competitors, related products and services, marketing st...
José Palazzo Moreira de Oliveira, Stanley L...