Paper Info
Title
Supporting Arabic cross-lingual retrieval using contextual information
Abstract
One of the main problems that impact the performance of cross-language information retrieval (CLIR) systems is how to disambiguate translations and - since this usually can not be done completely automatic - how to smoothly integrate a user in this disambiguation process. In order to ensure that a user has a certain confidence in selecting a translation she/he possibly can not even read or understand, we have to make sure that the system has provided sufficient information about translation alternatives and their meaning. In this paper, we present a CLIR tool that automatically translates the user query and provides possibilities to interactively select relevant terms using contextual information. This information is obtained from a parallel corpus to describe the translation in the user's query language. Furthermore, a user study was conducted to identify weaknesses in both disambiguation algorithm and interface design. The outcome of this user study leads to a much clearer view of how and what CLIR should offer to users.
Year
DOI
Venue
2011
10.1007/978-3-642-21353-3_4
IRFC
Keywords
Field
DocType
query language,clir tool,cross-language information retrieval,translation alternative,user study,sufficient information,user query,contextual information,disambiguation process,arabic cross-lingual retrieval,disambiguation algorithm
Data mining,Cross lingual,Contextual information,Query language,Arabic,Information retrieval,Computer science,Artificial intelligence,Natural language processing,Word-sense disambiguation,Interface design
Conference
Volume
ISSN
Citations 
6653
0302-9743
3
PageRank 
References 
Authors
0.37
17
3
Name
Order
Citations
PageRank
Farag Ahmed1282.87
Andreas Nürnberger2960103.52
Marcus Nitsche3306.27