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dc.contributor.advisorMichael Stonebraker.en_US
dc.contributor.authorWong, Brian Wai Fungen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2011-02-23T14:35:50Z
dc.date.available2011-02-23T14:35:50Z
dc.date.copyright2010en_US
dc.date.issued2010en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/61246
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (p. 79-80).en_US
dc.description.abstractThe 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.en_US
dc.description.statementofresponsibilityby Brian Wai Fung Wong.en_US
dc.format.extent80 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleDeep-web search engine ranking algorithmsen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.identifier.oclc701735206en_US


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