Title
Mining and Exploiting Domain-Specific Corpora in the PANACEA Platform
Abstract
The objective of the PANACEA ICT-2007.2.2 EU project is to build a platform that automates the stages involved in the acquisition, production, updating and maintenance of the large language resources required by, among others, MT systems. The development of a Corpus Acquisition Component (CAC) for extracting monolingual and bilingual data from the web is one of the most innovative building blocks of PANACEA. The CAC, which is the first stage in the PANACEA pipeline for building Language Resources, adopts an efficient and distributed methodology to crawl for web documents with rich textual content in specific languages and predefined domains. The CAC includes modules that can acquire parallel data from sites with in-domain content available in more than one language. In order to extrinsically evaluate the CAC methodology, we have conducted several experiments that used crawled parallel corpora for the identification and extraction of parallel sentences using sentence alignment. The corpora were then successfully used for domain adaptation of Machine Translation Systems.
Year
Venue
Keywords
2013
CoRR
grammar,greek language,educational technology,natural language processing,language assessment,human language technology,information,speech synthesis,morphology,semantics,sign language,ontologies,syntax,multimedia,data mining,lemmatizer,information retrieval,dictionary,machine translation,information extraction,speech recognition,computational linguistics
Field
DocType
Volume
Ontology (information science),Greeklish,Computer science,Machine translation,Computational linguistics,Panacea (medicine),Information extraction,Artificial intelligence,Natural language processing,Language technology,Semantics
Journal
abs/1303.1932
ISSN
Citations 
PageRank 
Proceedings of the 5th Workshop on Building and Using Comparable Corpora at the Eighth International Conference on Language Resources and Evaluation (LREC-2012); 2012 May 23-25; Istanbul, Turkey. Paris: ELRA; 2012. p. 24-26
2
0.38
References 
Authors
4
5
Name
Order
Citations
PageRank
Núria Bel120831.83
Vassilis Papavassiliou212010.74
Prokopis311410.95
Antonio Toral44710.43
Victoria Arranz54918.75