DEQA: deep web extraction for question answering

ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part II(2012)

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摘要
Despite decades of effort, intelligent object search remains elusive. Neither search engine nor semantic web technologies alone have managed to provide usable systems for simple questions such as "find me a flat with a garden and more than two bedrooms near a supermarket." We introduce deqa, a conceptual framework that achieves this elusive goal through combining state-of-the-art semantic technologies with effective data extraction. To that end, we apply deqa, to the UK real estate domain and show that it can answer a significant percentage of such questions correctly. deqa achieves this by mapping natural language questions to Sparql patterns. These patterns are then evaluated on an RDF database of current real estate offers. The offers are obtained using OXPath, a state-of-the-art data extraction system, on the major agencies in the Oxford area and linked through Limes to background knowledge such as the location of supermarkets.
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关键词
state-of-the-art data extraction system,oxford area,intelligent object search,effective data extraction,current real estate offer,question answering,search engine,uk real estate domain,elusive goal,semantic web technology,deep web extraction,state-of-the-art semantic technology,deep web
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