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CIKM
2010
Springer
13 years 5 months ago
Mining topic-level influence in heterogeneous networks
Influence is a complex and subtle force that governs the dynamics of social networks as well as the behaviors of involved users. Understanding influence can benefit various applic...
Lu Liu, Jie Tang, Jiawei Han, Meng Jiang, Shiqiang...
AINA
2008
IEEE
14 years 2 months ago
Opportunistic Data Dissemination Using Real-World User Mobility Traces
— Opportunistic communication allows humans equipped with mobile devices to exchange information via a wireless link whenever they are nearby. This work examines the performance ...
Andreas Heinemann, Jussi Kangasharju, Max Müh...
KDD
2009
ACM
179views Data Mining» more  KDD 2009»
14 years 2 months ago
Identifying graphs from noisy and incomplete data
There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biologic...
Galileo Mark S. Namata Jr., Lise Getoor
CIKM
2011
Springer
12 years 7 months ago
Towards feature selection in network
Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
Quanquan Gu, Jiawei Han

Publication
397views
14 years 9 months ago
Build it but where? A GIS methodology for guiding the planning of new cycling facilities
Concern over climate change, traffic congestion, and the health consequences of sedentary lifestyles has resulted in a surge of interest in cycling as an efficient form of urban ...
Larsen, J. & El-Geneidy, M.