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    A High Precision Information Retrieval Method for WiQA

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    Authors
    Orasan, Constantin
    Puşcaşu, Georgiana
    Issue Date
    2007
    
    Metadata
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    Abstract
    This paper presents Wolverhampton University’s participation in the WiQA competition. The method chosen for this task combines a high precision, but low recall information retrieval approach with a greedy sentence ranking algorithm. The high precision retrieval is ensured by querying the search engine with the exact topic, in this way obtaining only sentences which contain the topic. In one of the runs, the set of retrieved sentences is expanded using coreferential relations between sentences. The greedy algorithm used for ranking selects one sentence at a time, always the one which adds most information to the set of sentences without repeating the existing information too much. The evaluation revealed that it achieves a performance similar to other systems participating in the competition and that the run which uses coreference obtains the highest MRR score among all the participants.
    Citation
    In: Evaluation of Multilingual and Multi-modal Information Retrieval: 561-568
    Publisher
    Springer
    URI
    http://hdl.handle.net/2436/27916
    DOI
    10.1007/978-3-540-74999-8
    Type
    Chapter in book
    Language
    en
    Description
    7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain, September 20-22, 2006, Revised Selected Papers
    ISBN
    978-3-540-74998-1
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-540-74999-8
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    Research Institute in Information and Language Processing

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