French-English Terminology Extraction from Comparable Corpora

Daille, Béatrice; Morin, Emmanuel

doi:10.1007/11562214_62

Cited by 22 publications

(20 citation statements)

References 12 publications

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“…One such problem is word sense disambiguation and the translation of compound words as described in Daille and Morin (2005) and Morin et al (2007). In addition, indirect relations have been used in other tasks, such as paraphrase acquisition from bilingual parallel corpora (Kok and Brockett 2010).…”

Section: Resultsmentioning

confidence: 99%

Extracting Translation Pairs from Comparable Corpora through Graph-based Label Propagation

Tamura

Watanabe

Sumita

et al. 2013

Journal of Natural Language Processing

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This paper proposes a novel method for bilingual lexicon extraction from comparable corpora using graph-based label propagation. A previous study found that performance drastically decreases when the coverage of a seed lexicon is small. We address this problem by using indirect relations with bilingual seeds together with direct relations, in which each word is represented by a distribution of lexical seeds. The seed distributions are propagated over a graph that represents relations among words. Translation pairs are extracted by identifying word pairs with high similarities in the seed distributions. We propose two types of graphs: (1) a co-occurrence graph, representing co-occurrence relations between words; and (2) a similarity graph, representing context similarities between words. Evaluations on comparable corpora of English and Japanese patent documents show that our proposed graph propagation method outperforms conventional methods. Further, the similarity graph improved performance by clustering synonyms into the same translation.

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Section: Resultsmentioning

confidence: 99%

Extracting Translation Pairs from Comparable Corpora through Graph-based Label Propagation

Tamura

Watanabe

Sumita

et al. 2013

Journal of Natural Language Processing

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“…Déjean et al (2002) enriched the translation matrix prepared from an available dictionary with a hierarchical multilingual thesaurus. A number of studies (Daille and Morin 2005;Robitaille et al 2006) augmented this approach with techniques for multi-word recognition and alignment to extract equivalents for multi-word expressions from comparable corpora.…”

Section: Related Workmentioning

confidence: 98%

Finding translations for low-frequency words in comparable corpora

Pekar

Mitkov

Blagoev

et al. 2006

Machine Translation

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Statistical methods to extract translational equivalents from non-parallel corpora hold the promise of ensuring the required coverage and domain customisation of lexicons as well as accelerating their compilation and maintenance. A challenge for these methods are rare, less common words and expressions, which often have low corpus frequencies. However, it is rare words such as newly introduced terminology and named entities that present the main interest for practical lexical acquisition. In this article, we study possibilities of improving the extraction of low-frequency equivalents from bilingual comparable corpora. Our work is carried out in the general framework which discovers equivalences between words of different languages using similarities between their occurrence patterns found in respective monolingual corpora. We develop a method that aims to compensate for insufficient amounts of corpus evidence on rare words: prior to measuring cross-language similarities, the method uses same-language corpus data to model co-occurrence vectors of rare words by predicting their unseen co-occurrences and smoothing rare, unreliable ones. Our experimental evaluation demonstrates that the proposed method delivers a consistent and significant improvement on the conventional approach to this task.V. Pekar · R. Mitkov (B) ILP,

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“…Sun, Jin & Du extract bilingual terminology dictionary from English and Chinese parallel corpus automatically [2] . Daille & Morin extract French-English bilingual terminology from comparable corpus [3] . Zhang, Sun, Li et al extract special domain bilingual dictionary from non-parallel corpus, and the result shows that the quantity and frequency of seed words have a positive effect on the result of terms extraction [4] .…”

Section: (1) Bilingual Terminology Extractionmentioning

confidence: 99%

Extracting Chinese-English Bilingual Core Terminology from Parallel Classified Corpora in Special Domain

Zhang

2009

2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology

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The bilingual core terminology is the key resource for bilingual terminology extraction. In this paper, the keywords lists of the document in special domain are used to extract the candidate core terminology. After the keywords extraction and termhood computation, the core terminologies are extracted from the classified corpora in special domain respectively. Then, the bilingual terminology alignment method is used to extract the bilingual core terminology from the parallel classified corpora in special domain. The experiment result shows that the proposed method can be used to extract the Chinese-English core terminology quickly and efficiently.

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French-English Terminology Extraction from Comparable Corpora

Cited by 22 publications

References 12 publications

Extracting Translation Pairs from Comparable Corpora through Graph-based Label Propagation

Extracting Translation Pairs from Comparable Corpora through Graph-based Label Propagation

Finding translations for low-frequency words in comparable corpora

Extracting Chinese-English Bilingual Core Terminology from Parallel Classified Corpora in Special Domain

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