Knowledge Discovery from Data (TKDD)


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ACM Transactions on Knowledge Discovery from Data (TKDD) - Casin special issue, Volume 8 Issue 1, February 2014

Introduction to special issue on computational aspects of social and information networks: Theory, methodologies, and applications (TKDD-CASIN)
Wei Chen, Jie Tang
Article No.: 1
DOI: 10.1145/2556608

Uncovering social network Sybils in the wild
Zhi Yang, Christo Wilson, Xiao Wang, Tingting Gao, Ben Y. Zhao, Yafei Dai
Article No.: 2
DOI: 10.1145/2556609

Sybil accounts are fake identities created to unfairly increase the power or resources of a single malicious user. Researchers have long known about the existence of Sybil accounts in online communities such as file-sharing systems, but they have...

Scalable and axiomatic ranking of network role similarity
Ruoming Jin, Victor E. Lee, Longjie Li
Article No.: 3
DOI: 10.1145/2518176

A key task in analyzing social networks and other complex networks is role analysis: describing and categorizing nodes according to how they interact with other nodes. Two nodes have the same role if they interact with equivalent sets of...

Discovering social circles in ego networks
Julian Mcauley, Jure Leskovec
Article No.: 4
DOI: 10.1145/2556612

People's personal social networks are big and cluttered, and currently there is no good way to automatically organize them. Social networking sites allow users to manually categorize their friends into social circles (e.g., “circles”...

A separability framework for analyzing community structure
Bruno Abrahao, Sucheta Soundarajan, John Hopcroft, Robert Kleinberg
Article No.: 5
DOI: 10.1145/2527231

Four major factors govern the intricacies of community extraction in networks: (1) the literature offers a multitude of disparate community detection algorithms whose output exhibits high structural variability across the collection, (2)...

User behavior learning and transfer in composite social networks
Erheng Zhong, Wei Fan, Qiang Yang
Article No.: 6
DOI: 10.1145/2556613

Accurate prediction of user behaviors is important for many social media applications, including social marketing, personalization, and recommendation. A major challenge lies in that although many previous works model user behavior from only...