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KDD
2012
ACM
221views Data Mining» more  KDD 2012»
13 years 9 months ago
Fast mining and forecasting of complex time-stamped events
Given huge collections of time-evolving events such as web-click logs, which consist of multiple attributes (e.g., URL, userID, timestamp), how do we find patterns and trends? Ho...
Yasuko Matsubara, Yasushi Sakurai, Christos Falout...
KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 9 months ago
Low rank modeling of signed networks
Trust networks, where people leave trust and distrust feedback, are becoming increasingly common. These networks may be regarded as signed graphs, where a positive edge weight cap...
Cho-Jui Hsieh, Kai-Yang Chiang, Inderjit S. Dhillo...
KDD
2012
ACM
187views Data Mining» more  KDD 2012»
13 years 9 months ago
Online learning to diversify from implicit feedback
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
Karthik Raman, Pannaga Shivaswamy, Thorsten Joachi...
KDD
2012
ACM
164views Data Mining» more  KDD 2012»
13 years 9 months ago
SeqiBloc: mining multi-time spanning blockmodels in dynamic graphs
Blockmodelling is an important technique for decomposing graphs into sets of roles. Vertices playing the same role have similar patterns of interactions with vertices in other rol...
Jeffrey Chan, Wei Liu, Christopher Leckie, James B...
KDD
2012
ACM
229views Data Mining» more  KDD 2012»
13 years 9 months ago
Finding trendsetters in information networks
Influential people have an important role in the process of information diffusion. However, there are several ways to be influential, for example, to be the most popular or the...
Diego Sáez-Trumper, Giovanni Comarela, Virg...