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dc.contributor.authorOrasan, Constantinen_GB
dc.contributor.authorPuşcaşu, Georgianaen_GB
dc.date.accessioned2013-06-27T15:51:40Z
dc.date.available2013-06-27T15:51:40Z
dc.date.issued2007
dc.identifier.citationIn: Evaluation of Multilingual and Multi-modal Information Retrieval: 561-568en_GB
dc.identifier.isbn978-3-540-74998-1
dc.identifier.doi10.1007/978-3-540-74999-8
dc.identifier.urihttp://hdl.handle.net/2384/294828
dc.description.abstractThis 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.en_GB
dc.publisherSpringeren_GB
dc.titleA High Precision Information Retrieval Method for WiQAen_GB
dc.typeBook Chapteren


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