The problem of eciently retrieving and ranking documents from a huge collection according to their relevance to a research topic is addressed. A broad class of queries is dened a...
In recent years, the language model Latent Dirichlet Allocation (LDA), which clusters co-occurring words into topics, has been widely applied in the computer vision field. Howeve...
In this paper, we describe a document clustering method called noveltybased document clustering. This method clusters documents based on similarity and novelty. The method assigns...
Entity detection and tracking is a relatively new addition to the repertoire of natural language tasks. In this paper, we present a statistical language-independent framework for ...
Radu Florian, Hany Hassan, Abraham Ittycheriah, Ho...
Several phrase chunkers have been proposed over the past few years. Some state-of-the-art chunkers achieved better performance via integrating external resources, e.g., parsers and...