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ICDM
2008
IEEE
117views Data Mining» more  ICDM 2008»
13 years 11 months ago
RTM: Laws and a Recursive Generator for Weighted Time-Evolving Graphs
How do real, weighted graphs change over time? What patterns, if any, do they obey? Earlier studies focus on unweighted graphs, and, with few exceptions, they focus on static snap...
Leman Akoglu, Mary McGlohon, Christos Faloutsos
IPPS
2008
IEEE
13 years 11 months ago
Parallel mining of closed quasi-cliques
Graph structure can model the relationships among a set of objects. Mining quasi-clique patterns from large dense graph data makes sense with respect to both statistic and applica...
Yuzhou Zhang, Jianyong Wang, Zhiping Zeng, Lizhu Z...
BMCBI
2008
208views more  BMCBI 2008»
13 years 5 months ago
GraphFind: enhancing graph searching by low support data mining techniques
Background: Biomedical and chemical databases are large and rapidly growing in size. Graphs naturally model such kinds of data. To fully exploit the wealth of information in these...
Alfredo Ferro, Rosalba Giugno, Misael Mongiov&igra...
ICDM
2009
IEEE
202views Data Mining» more  ICDM 2009»
13 years 2 months ago
Link Prediction on Evolving Data Using Matrix and Tensor Factorizations
Abstract--The data in many disciplines such as social networks, web analysis, etc. is link-based, and the link structure can be exploited for many different data mining tasks. In t...
Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda
ICDM
2010
IEEE
186views Data Mining» more  ICDM 2010»
13 years 3 months ago
MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model
Human emotion is one important underlying force affecting and affected by the dynamics of social networks. An interesting question is "can we predict a person's mood base...
Yuan Zhang, Jie Tang, Jimeng Sun, Yiran Chen, Jing...