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» Learning and Predicting the Evolution of Social Networks
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CORR
2010
Springer
147views Education» more  CORR 2010»
13 years 10 months ago
Modeling the structure and evolution of discussion cascades
We analyze the structure and evolution of discussion cascades in four popular websites: Slashdot, Barrapunto, Meneame and Wikipedia. Despite the big heterogeneities between these ...
Vicenç Gómez, Hilbert J. Kappen, And...
CIKM
2010
Springer
13 years 7 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...
WMTE
2005
IEEE
14 years 3 months ago
G1: 1 Scenarios: Envisioning the Context for WMTE in 2015
The G1:1 international network of learning researchers met to identify major trends and uncertainties that could drive the evolution of learning technology. Using a technique call...
Jeremy Roschelle, Charles Patton, John Brecht, Mar...
KDD
2009
ACM
180views Data Mining» more  KDD 2009»
14 years 10 months ago
Mining social networks for personalized email prioritization
Email is one of the most prevalent communication tools today, and solving the email overload problem is pressingly urgent. A good way to alleviate email overload is to automatical...
Shinjae Yoo, Yiming Yang, Frank Lin, Il-Chul Moon
ATAL
2010
Springer
13 years 11 months ago
Frequency adjusted multi-agent Q-learning
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Michael Kaisers, Karl Tuyls