Transitive probabilistic CLIR models

Transitive probabilistic CLIR models (2004)

by Wessel Kraaij , Franciska De Jong

Venue:	In Proceedings of RIAO 2004: Recherche d’Informations Assistee par Ordinateur
Citations:	5 - 2 self

Datum	Value	Source
TITLE	Transitive probabilistic CLIR models	SVM HeaderParse 0.2
AUTHOR NAME	Wessel Kraaij	SVM HeaderParse 0.2
AUTHOR AFFIL	TNO TPD	SVM HeaderParse 0.2
AUTHOR NAME	Franciska De Jong	SVM HeaderParse 0.2
AUTHOR AFFIL	Universiteit Twente, dept. of Computer Science	SVM HeaderParse 0.2
AUTHOR ADDR	P.O. Box 217	SVM HeaderParse 0.2
ABSTRACT	Transitive translation could be a useful technique to enlarge the number of supported language pairs for a cross-language information retrieval (CLIR) system in a cost-effective manner. The paper describes several setups for transitive translation based on probabilistic translation models. The transitive CLIR models were evaluated on the CLEF test collection and yielded a retrieval effectiveness up to 83 % of monolingual performance, which is significantly better than a baseline using the synonym operator. 1	SVM HeaderParse 0.2
YEAR	2004	INFERENCE
VENUE	In Proceedings of RIAO 2004: Recherche d’Informations Assistee par Ordinateur	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
CITATIONS	28 found	ParsCit 1.0