We propose a new unsupervised learning technique for extracting information about authors and topics from large text collections. We model documents as if they were generated by a...
Michal Rosen-Zvi, Chaitanya Chemudugunta, Thomas L...
We argue that the quality of a summary can be evaluated based on how many concepts in the original document(s) that reserved after summarization. Here, a concept refers to an abst...
A novel method for simultaneous keyphrase extraction and generic text summarization is proposed by modeling text documents as weighted undirected and weighted bipartite graphs. Sp...
Given a video and associated text, we propose an automatic annotation scheme in which we employ a latent topic model to generate topic distributions from weighted text and then mo...
Chris Engels, Koen Deschacht, Jan Hendrik Becker, ...
Previous work has shown that high quality phrasal paraphrases can be extracted from bilingual parallel corpora. However, it is not clear whether bitexts are an appropriate resourc...
Juri Ganitkevitch, Chris Callison-Burch, Courtney ...