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    A Dynamic Programming Approach to Improving Translation Memory Matching and Retrieval Using Paraphrases

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    Authors
    Gupta, Rohit
    Orăsan, Constantin
    Liu, Qun
    Mitkov, Ruslan
    Editors
    Sojka, Petr
    Horak, Ales
    Kopecek, Ivan
    Issue Date
    2016-09
    
    Metadata
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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
    Citation
    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
    Publisher
    Springer
    URI
    http://hdl.handle.net/2436/620374
    Additional Links
    http://link.springer.com/chapter/10.1007%2F978-3-319-45510-5_30
    Type
    Chapter in book
    Language
    en
    ISBN
    9783319455099
    9783319455105 on-line
    Sponsors
    FP7/2007-2013/ under REA grant agreement no. 317471, Funded by: FP7 People Programme
    Collections
    Faculty of Social Sciences

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