LREC 2006 - Proceedings sorted by papers

Title	A Deep Linguistic Analysis for Cross-language Information Retrieval
Authors	N. Semmar, M. Laib, C. Fluhr
Abstract	Cross-language information retrieval consists in providing a query in one language and searching documents in one or different languages. These documents are ordered by the probability of being relevant to the user's request. The highest ranked document is considered to be the most likely relevant document. The LIC2M cross-language information retrieval system is a weighted Boolean search engine based on a deep linguistic analysis of the query and the documents. This system is composed of a linguistic analyzer, a statistic analyzer, a reformulator, a comparator and a search engine. The linguistic analysis processes both documents to be indexed and queries to extract concepts representing their content. This analysis includes a morphological analysis, a part-of-speech tagging and a syntactic analysis. In this paper, we present the deep linguistic analysis used in the LIC2M cross-lingual search engine and we will particularly focus on the impact of the syntactic analysis on the retrieval effectiveness.
Keywords	Morphological analysis, part-of-speech tagging, syntactic analysis, named entities, cross-lingual information retrieval
Full paper	A Deep Linguistic Analysis for Cross-language Information Retrieval

Title

A Deep Linguistic Analysis for Cross-language Information Retrieval

Authors

N. Semmar, M. Laib, C. Fluhr

Abstract

Cross-language information retrieval consists in providing a query in one language and searching documents in one or different languages. These documents are ordered by the probability of being relevant to the user's request. The highest ranked document is considered to be the most likely relevant document. The LIC2M cross-language information retrieval system is a weighted Boolean search engine based on a deep linguistic analysis of the query and the documents. This system is composed of a linguistic analyzer, a statistic analyzer, a reformulator, a comparator and a search engine. The linguistic analysis processes both documents to be indexed and queries to extract concepts representing their content. This analysis includes a morphological analysis, a part-of-speech tagging and a syntactic analysis. In this paper, we present the deep linguistic analysis used in the LIC2M cross-lingual search engine and we will particularly focus on the impact of the syntactic analysis on the retrieval effectiveness.

Keywords

Morphological analysis, part-of-speech tagging, syntactic analysis, named entities, cross-lingual information retrieval

Full paper

A Deep Linguistic Analysis for Cross-language Information Retrieval