A High Precision Information Retrieval Method for WiQA
Orasan, Constantin Puşcaşu, Georgiana
Orasan, Constantin
Puşcaşu, Georgiana
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2007
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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.
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In: Evaluation of Multilingual and Multi-modal Information Retrieval: 561-568
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en
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7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain, September 20-22, 2006, Revised Selected Papers
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978-3-540-74998-1