Multidocument extractive summarization relies on the concept of sentence centrality to identify the most important sentences in a document. Centrality is typically defined in term...
We present the background and justi cation for a new approachto studying computation and computational complexity. We focus on categories of problems and categories of solutions w...
We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time. The classification model is...
This paper addresses the issue of extraction of an academic researcher social network. By researcher social network extraction, we are aimed at finding, extracting, and fusing the...
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...