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Pregled bibliografske jedinice broj: 552852

Bilingual Lexicon Extraction from Comparable Corpora for Closely Related Languages


Fišer, Darja; Ljubešić, Nikola
Bilingual Lexicon Extraction from Comparable Corpora for Closely Related Languages // Proceedings of the International Conference Recent Advances in Natural Language Processing 2011
Hissar, Bulgaria: RANLP 2011 Organising Committee, 2011. str. 125-131 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Bilingual Lexicon Extraction from Comparable Corpora for Closely Related Languages

Autori
Fišer, Darja ; Ljubešić, Nikola

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011 / - Hissar, Bulgaria : RANLP 2011 Organising Committee, 2011, 125-131

Skup
Recent Advances in Natural Language Processing 2011

Mjesto i datum
Hissar, Bugarska, 12-14.09.2011.

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Comparable corpora; lexicon extraction; closely related languages

Sažetak
In this paper we present a knowledge-light approach to extract a bilingual lexicon for closely related languages from comparable corpora. While in most related work an existing dictionary is used to translate context vectors, we take advantage of the similarities between languages instead and build a seed lexicon from words that are identical in both languages and then further extend it with context-based cognates and translations of the most frequent words. We also use cognates for reranking translation candidates obtained via context similarity and extract translation equivalents for all content words, not just nouns as in most related work. The results are very encouraging, suggesting that other similar languages could bene- fit from the same approach. By enlarging the seed lexicon with cognates and translations of the most frequent words and by cognate-based reranking of translation candidates we were able to improve the average baseline precision from 0.592 to 0.797 on the mean reciprocal rank for the ten top- ranking translation candidates for nouns, verbs and adjectives with a 46% recall on the gold standard of 1000 random entries from a traditional dictionary.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



POVEZANOST RADA


Projekt / tema
130-1301679-1380 - Hrvatska rječnička baština i hrvatski europski identitet (Damir Boras, )

Ustanove
Filozofski fakultet, Zagreb

Autor s matičnim brojem:
Nikola Ljubešić, (272820)