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Query-By-Structure Approach for the Web
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Author(s): Michael Johnson (Madonna University, USA), Farshad Fotouhi (Wayne State University, USA)and Sorin Draghici (Wayne State University, USA)
Copyright: 2003
Pages: 22
Source title:
Data Mining: Opportunities and Challenges
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-051-6.ch013
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Abstract
This chapter presents three systems that incorporate document structure information into a search of the Web. These systems extend existing Web searches by allowing the user to request documents containing not only specific search words, but also to specify that documents be of a certain type. In addition to being able to search a local database (DB), all three systems are capable of dynamically querying the Web. Each system applies a query-by-structure approach that captures and utilizes structure information as well as content during a query of the Web. Two of the systems also employ neural networks (NNs) to organize the information based on relevancy of both the content and structure. These systems utilize a supervised Hamming NN and an unsupervised competitive NN, respectively. Initial testing of these systems has shown promising results when compared to straight keyword searches.
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