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...
In this paper, we investigate the problem of improving the relevance of a Web search engine by adapting it to the dynamic needs of the user. We examine a representative case of su...
Every day millions of users search for information on the web via search engines, and provide implicit feedback to the results shown for their queries by clicking or not onto them...
Carlos Castillo, Claudio Corsi, Debora Donato, Pao...
The presence of Web spam in query results is one of the critical challenges facing search engines today. While search engines try to combat the impact of spam pages on their resul...
Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate...
As more information becomes available on the World Wide Web, it has become an acute problem to provide effective search tools for information access. Previous generations of search...
This paper addresses the problem of categorizing terms or lexical entities into a predefined set of semantic domains exploiting the knowledge available on-line in the Web. The prop...
Leonardo Rigutini, Ernesto Di Iorio, Marco Ernande...
We here describe the subword approach we used in the 2006 ImageCLEF Medical Image Retrieval task. It is based on the assupmtion that neither fully inflected nor automatically stem...
Abstract. We combine in this paper automatic learning of a large lexicon of semantic concepts with traditional video retrieval methods into a novel approach to narrow the semantic ...
Cees Snoek, Marcel Worring, Dennis Koelma, Arnold ...
This work addresses two common problems in search, frequently occurring with underspecified user queries: the top-ranked results for such queries may not contain documents relevan...