Copyright 1995 INIST-CNRS CC BY 4.0 Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Sciences of information and communication. Documentation
FRANCIS
Accession Number:
edscal.3461416
Database:
PASCAL Archive
Weitere Informationen
This paper reports on some revent developments in our natural language text retrieval system. The system uses advanced natural language processing techniques to enhance the effectiveness of term-based document retrieval. Th backbone of our system is a traditional statistical engine which builds inverted index files from pre-processed documents and then searches and ranks the documents in response to user queries. Natural language processing is used to (1) preprocess the document in order to extract content-carrying term, (2) discover inter-term dependencies and build a conceptual hierarchy specific to the database domain, and (3) process user's natural language requests into effective search queries. While the general desigh of the system has not changed since TREC-2 conference, we nonetheless replaced several components and added a number of new features which are describes in the present paper. While the general design of the system has not changed since TREC-1 conference, we nonetheless replaced several components and added a number of new features which are described in the present paper.