A Dynamic Programming Approach to Improving Translation Memory Matching and Retrieval Using Paraphrases
Gupta, Rohit Orăsan, Constantin Liu, Qun Mitkov, Ruslan
Gupta, Rohit
Orăsan, Constantin
Liu, Qun
Mitkov, Ruslan
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2016-09
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Abstract
Translation memory tools lack semantic knowledge like paraphrasing when they perform matching and retrieval. As a result, paraphrased segments are often not retrieved. One of the primary reasons for this is the lack of a simple and efficient algorithm to incorporate paraphrasing in the TM matching process. Gupta and Orăsan [1] proposed an algorithm which incorporates paraphrasing based on greedy approximation and dynamic programming. However, because of greedy approximation, their approach does not make full use of the paraphrases available. In this paper we propose an efficient method for incorporating paraphrasing in matching and retrieval based on dynamic programming only. We tested our approach on English-German, English-Spanish and English-French language pairs and retrieved better results for all three language pairs compared to the earlier approach
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In: Petr Sojka, Aleš Horák, Ivan Kopeček, Karel Pala (eds), Text, Speech, and Dialogue: olume 9924 of the series Lecture Notes in Computer Science pp 259-269
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en
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9783319455099
9783319455105 on-line
9783319455105 on-line
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FP7/2007-2013/ under REA grant agreement no. 317471, Funded by: FP7 People Programme