We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
We analyze a massive social network, gathered from the records of a large mobile phone operator, with more than a million users and tens of millions of calls. We examine the distr...
This work introduces a new family of link-based dissimilarity measures between nodes of a weighted directed graph. This measure, called the randomized shortest-path (RSP) dissimil...
Luh Yen, Marco Saerens, Amin Mantrach, Masashi Shi...
We propose a new method for detecting patterns of anomalies in categorical datasets. We assume that anomalies are generated by some underlying process which affects only a particu...
Along with the blossom of open source projects comes the convenience for software plagiarism. A company, if less self-disciplined, may be tempted to plagiarize some open source pr...
Chao Liu 0001, Chen Chen, Jiawei Han, Philip S. Yu