Knowledge Discovery from Data (TKDD)


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ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 3 Issue 2, April 2009

Introduction to special issue on social computing, behavioral modeling, and prediction
Huan Liu, John Salerno, Michael Young, Rakesh Agrawal, Philip S. Yu
Article No.: 6
DOI: 10.1145/1514888.1514889

Expanding network communities from representative examples
Andrew Mehler, Steven Skiena
Article No.: 7
DOI: 10.1145/1514888.1514890

We present an approach to leverage a small subset of a coherent community within a social network into a much larger, more representative sample. Our problem becomes identifying a small conductance subgraph containing many (but not necessarily...

Analyzing communities and their evolutions in dynamic social networks
Yu-Ru Lin, Yun Chi, Shenghuo Zhu, Hari Sundaram, Belle L. Tseng
Article No.: 8
DOI: 10.1145/1514888.1514891

We discover communities from social network data and analyze the community evolution. These communities are inherent characteristics of human interaction in online social networks, as well as paper citation networks. Also, communities may evolve...

Blocking links to minimize contamination spread in a social network
Masahiro Kimura, Kazumi Saito, Hiroshi Motoda
Article No.: 9
DOI: 10.1145/1514888.1514892

We address the problem of minimizing the propagation of undesirable things, such as computer viruses or malicious rumors, by blocking a limited number of links in a network, which is converse to the influence maximization problem in which the most...

Modeling information-seeker satisfaction in community question answering
Eugene Agichtein, Yandong Liu, Jiang Bian
Article No.: 10
DOI: 10.1145/1514888.1514893

Question Answering Communities such as Naver, Baidu Knows, and Yahoo! Answers have emerged as popular, and often effective, means of information seeking on the web. By posting questions for other participants to answer, information seekers...