Abstract
A new method of search data on Deep Web is proposed in this paper based on the concept of domain knowledge and the feature of Deep Web data. First they obtain the search interfaces on the Deep Web; and then do feature analysis and domain judge on them; at last, they classify and integrate various interfaces in line with diverse domains. This method has showed up higher degree of correlation of domains from the seek result, via testing several different domains. Compared with other methods, its recall and precision are also satisfactory.
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© 2012 Springer-Verlag Berlin Heidelberg
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Rong, D., Hao, W., Xin, Z. (2012). The Design of Deep Web Search Engine Based on Domain Knowledge. In: Deng, W. (eds) Future Control and Automation. Lecture Notes in Electrical Engineering, vol 173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31003-4_40
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DOI: https://doi.org/10.1007/978-3-642-31003-4_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31002-7
Online ISBN: 978-3-642-31003-4
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