A Conceptual Representation of Documents and Queries for Information Retrieval Based on Light Ontologies

The classification task and retrieval task are developed based on the distributional representation of the text by utilizing term - document matrix and non-negative

With the objective to build a health search engine, task 2 of 2015 CLEF eHealth aims to detect levels of ac- curacy of information retrieval systems when searching for web

In this work we focus on data ex- traction and data visualization for information retrieval sys- tems, i.e., how to extract data from the sources of inter- est in a convenient way,

It has been proven that the textual entailment judgment may improve the performance of the hypothesis validation, given a support text, which in this case is the retrieved

Even if query building and indexing are evaluated jointly in the present task, it is fairly obvious that it is the quality of queries that is lacking in Lexware ® and not the

At CLEF 2001, we participated in the monolingual, bilingual, and multilingual tasks. Our interest in monolin- gual task is to test the idea of treating the German decompounding

Using the tools described above, the ex- tended ontology and a richer set of relationships, the semantic infrastructure will support functional interoperability [5] through

This paper presents a vector space model approach, for rep- resenting documents and queries, using concepts instead of terms and WordNet as a light ontology.. This way, informa-