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KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 3 months ago
Sampling from large graphs
Given a huge real graph, how can we derive a representative sample? There are many known algorithms to compute interesting measures (shortest paths, centrality, betweenness, etc.)...
Jure Leskovec, Christos Faloutsos
119
Voted
KDD
2003
ACM
122views Data Mining» more  KDD 2003»
16 years 3 months ago
Discovery of climate indices using clustering
To analyze the effect of the oceans and atmosphere on land climate, Earth Scientists have developed climate indices, which are time series that summarize the behavior of selected ...
Michael Steinbach, Pang-Ning Tan, Vipin Kumar, Ste...
155
Voted
CIKM
2009
Springer
15 years 8 months ago
Probabilistic models for topic learning from images and captions in online biomedical literatures
Biomedical images and captions are one of the major sources of information in online biomedical publications. They often contain the most important results to be reported, and pro...
Xin Chen, Caimei Lu, Yuan An, Palakorn Achananupar...
134
Voted
PKDD
1999
Springer
106views Data Mining» more  PKDD 1999»
15 years 7 months ago
Heuristic Measures of Interestingness
When mining a large database, the number of patterns discovered can easily exceed the capabilities of a human user to identify interesting results. To address this problem, variou...
Robert J. Hilderman, Howard J. Hamilton
149
Voted
WSDM
2012
ACM
304views Data Mining» more  WSDM 2012»
13 years 11 months ago
Beyond co-occurrence: discovering and visualizing tag relationships from geo-spatial and temporal similarities
Studying relationships between keyword tags on social sharing websites has become a popular topic of research, both to improve tag suggestion systems and to discover connections b...
Haipeng Zhang, Mohammed Korayem, Erkang You, David...