Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...
Television news has become the predominant way of understanding the world around us, but individual news broadcasters can frame or mislead an audience’s understanding of politic...
Term-based representations of documents have found widespread use in information retrieval. However, one of the main shortcomings of such methods is that they largely disregard le...
This paper presents a means of automatically deriving a hierarchical organization of concepts from a set of documents without use of training data or standard clustering technique...
This work focusses on bridging between folksonomies, which provide social but mainly flat and unstructured metadata on web resources, and semantic web ontologies, which instead des...