Supervised topic models utilize document's side information for discovering predictive low dimensional representations of documents; and existing models apply likelihoodbased...
In this paper we study the problem of finding most topical named entities among all entities in a document, which we refer to as focused named entity recognition. We show that th...
This work provides algorithms and heuristics to index text documents by determining important topics in the documents. To index text documents, the work provides algorithms to gene...
This paper explores topic aspect (i.e., subtopic or facet) classification for English and Chinese collections. The evaluation model assumes a bilingual user who has found document...
Statistical language models can learn relationships between topics discussed in a document collection and persons, organizations and places mentioned in each document. We present a...
David Newman, Chaitanya Chemudugunta, Padhraic Smy...