2026-09-19T02:41:19Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/612462022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Michael Stonebraker.
Wong, Brian Wai Fung
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2011-02-23T14:35:50Z
2011-02-23T14:35:50Z
2010
2010
http://hdl.handle.net/1721.1/61246
701735206
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 79-80).
The deep web refers to content that is hidden behind HTML forms. The deep web contains a large collection of data that are unreachable by link-based search engines. A study conducted at University of California, Berkeley estimated that the deep web consists of around 91,000 terabytes of data, whereas the surface web is only about 167 terabytes. To access this content, one must submit valid input values to the HTML form. Several researchers have studied methods for crawling deep web content. One of the most promising methods uses unique wrappers for HTML forms. User inputs are first filtered through the wrappers before being submitted to the forms. However, this method requires a new algorithm for ranking search results generated by the wrappers. In this paper, I explore methods for ranking search results returned from a wrapped-based deep web search engine.
by Brian Wai Fung Wong.
M.Eng.
80 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Deep-web search engine ranking algorithms
Thesis
application/pdf
Publication
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unknown
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<Abstract>The deep web refers to content that is hidden behind HTML forms. The deep web contains a large collection of data that are unreachable by link-based search engines. A study conducted at University of California, Berkeley estimated that the deep web consists of around 91,000 terabytes of data, whereas the surface web is only about 167 terabytes. To access this content, one must submit valid input values to the HTML form. Several researchers have studied methods for crawling deep web content. One of the most promising methods uses unique wrappers for HTML forms. User inputs are first filtered through the wrappers before being submitted to the forms. However, this method requires a new algorithm for ranking search results generated by the wrappers. In this paper, I explore methods for ranking search results returned from a wrapped-based deep web search engine.</Abstract>
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