We argue that expert finding is sensitive to multiple document features in an organization, and therefore, can benefit from the incorporation of these document features. We propos...
In automated text categorization, given a small number of labeled documents, it is very challenging, if not impossible, to build a reliable classifier that is able to achieve high...
Zenglin Xu, Rong Jin, Kaizhu Huang, Michael R. Lyu...
This article is motivated by the importance of building web data mashups. Building on the remarkable success of Web 2.0 mashups, and specially Yahoo Pipes, we generalize the idea ...
Information retrieval systems (IRSs) usually suffer from a low ability to recognize a same idea that is expressed in different forms. A way of improving these systems is to take ...
Fabienne Moreau, Vincent Claveau, Pascale Sé...
In this poster, we propose a novel document summarization approach named Ontology-enriched M ulti-Document Summarization(OMS) for utilizing background knowledge to improve summari...