Paper Info
Title
Improving Bilingual Terminology Extraction from Comparable Corpora via Multiple Word-Space Models.
Abstract
There is a rich flora of word space models that have proven their efficiency in many different applications including information retrieval (Dumais et al., 1988), word sense disambiguation (Schutze, 1993), various semantic knowledge tests (Lund et al., 1995; Karlgren and Sahlgren, 2001), and text categorization (Sahlgren and Karlgren, 2005). Based on the assumption that each model captures some aspects of word meanings and provides its own empirical evidence, we present in this paper a systematic exploration of the principal corpus-based word space models for bilingual terminology extraction from comparable corpora. We find that, once we have identified the best procedures, a very simple combination approach leads to significant improvements compared to individual models.
Year
Venue
Keywords
2016
LREC 2016 - TENTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
Comparable corpora,Bilingual lexicon extraction,word-space models
Field
DocType
Citations 
Computer science,Speech recognition,Natural language processing,Artificial intelligence,Terminology extraction
Conference
0
PageRank 
References 
Authors
0.34
12
2
Name
Order
Citations
PageRank
Amir Hazem12510.18
Emmanuel Morin24216.13