Efficient bilingual lexicon extraction from comparable corpora based on formal concepts analysis. (4th January 2023)
- Record Type:
- Journal Article
- Title:
- Efficient bilingual lexicon extraction from comparable corpora based on formal concepts analysis. (4th January 2023)
- Main Title:
- Efficient bilingual lexicon extraction from comparable corpora based on formal concepts analysis
- Authors:
- Chebel, Mohamed
Latiri, Chiraz
Gaussier, Eric - Abstract:
- Abstract: Bilingual corpora are an essential resource used to cross the language barrier in multilingual natural language processing tasks. Among bilingual corpora, comparable corpora have been the subject of many studies as they are both frequent and easily available. In this paper, we propose to make use of formal concept analysis to first construct concept vectors which can be used to enhance comparable corpora through clustering techniques. We then show how one can extract bilingual lexicons of improved quality from these enhanced corpora. We finally show that the bilingual lexicons obtained can complement existing bilingual dictionaries and improve cross-language information retrieval systems.
- Is Part Of:
- Natural language engineering. Volume 29:Number 1(2023)
- Journal:
- Natural language engineering
- Issue:
- Volume 29:Number 1(2023)
- Issue Display:
- Volume 29, Issue 1 (2023)
- Year:
- 2023
- Volume:
- 29
- Issue:
- 1
- Issue Sort Value:
- 2023-0029-0001-0000
- Page Start:
- 138
- Page End:
- 161
- Publication Date:
- 2023-01-04
- Subjects:
- Corpus linguistics -- Evaluation -- Information extraction -- Information retrieval -- Multilinguality
Natural language processing (Computer science) -- Periodicals
Software engineering -- Periodicals
006.35 - Journal URLs:
- http://journals.cambridge.org/action/displayJournal?jid=NLE ↗
- DOI:
- 10.1017/S135132492100022X ↗
- Languages:
- English
- ISSNs:
- 1351-3249
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 26980.xml