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ICML
2003
IEEE

Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries

11 years 3 months ago
Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries
Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of entities. However, much of this work assumes that this underlying structure is known or can easily be inferred from data, which may often be an unrealistic assumption for many real-world problems. Below we consider the problem of learning and querying a graph-based model of this underlying structure. The model is learned from noisy observations linking sets of entities. We explicitly allow different types of links (representing different types of relations) and temporal information indicating when a link was observed. We quantitatively compare this representation and learning method against other algorithms on the task of predicting future links and new "friendships" in a variety of real world data sets.
Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G
Added 17 Nov 2009
Updated 17 Nov 2009
Type Conference
Year 2003
Where ICML
Authors Jeremy Kubica, Andrew W. Moore, David Cohn, Jeff G. Schneider
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