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• W944435052 abstract "To extract expert clinic information from the Deep Web, there are two challenges to face. The first one is to make a judgment on forms. A novel method based on a domain model, which is a tree structure constructed by the attributes of query interfaces is proposed. With this model, query interfaces can be classified to a domain and filled in with domain keywords. Another challenge is to extract information from response Web pages indexed by query interfaces. To filter the noisy information on a Web page, a block importance model is proposed, both content and spatial features are taken into account in this model. The experimental results indicate that the domain model yields a precision 4.89% higher than that of the rule-based method, whereas the block importance model yields an F1 measure 10.5% higher than that of the XPath method." @default.
• W944435052 created "2016-06-24" @default.
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• W944435052 date "2015-11-01" @default.
• W944435052 modified "2023-09-25" @default.
• W944435052 title "Clinic expert information extraction based on domain model and block importance model" @default.
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• W944435052 doi "https://doi.org/10.1016/j.compbiomed.2015.07.009" @default.
• W944435052 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/26231612" @default.
• W944435052 hasPublicationYear "2015" @default.
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