Document clustering techniques mostly rely on single term analysis of the document data set, such as the Vector Space Model. To better capture the structure of documents, the unde...
In this paper we propose two methods to derive two different kinds of node similarities in a network based on their neighborhood. The first similarity measure focuses on the overla...
In analyzing data from social and communication networks, we encounter the problem of classifying objects where there is an explicit link structure amongst the objects. We study t...
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
We describe a new scalable algorithm for semi-supervised training of conditional random fields (CRF) and its application to partof-speech (POS) tagging. The algorithm uses a simil...