Deep-web search engine ranking algorithms
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2011
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| Online Access: | http://hdl.handle.net/1721.1/61246 |
| _version_ | 1811083589730697216 |
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| author | Wong, Brian Wai Fung |
| author2 | Michael Stonebraker. |
| author_facet | Michael Stonebraker. Wong, Brian Wai Fung |
| author_sort | Wong, Brian Wai Fung |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. |
| first_indexed | 2024-09-23T12:35:29Z |
| format | Thesis |
| id | mit-1721.1/61246 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T12:35:29Z |
| publishDate | 2011 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/612462019-04-12T11:53:25Z Deep-web search engine ranking algorithms Wong, Brian Wai Fung Michael Stonebraker. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. 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. 2011-02-23T14:35:50Z 2011-02-23T14:35:50Z 2010 2010 Thesis http://hdl.handle.net/1721.1/61246 701735206 eng M.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. http://dspace.mit.edu/handle/1721.1/7582 80 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Wong, Brian Wai Fung Deep-web search engine ranking algorithms |
| title | Deep-web search engine ranking algorithms |
| title_full | Deep-web search engine ranking algorithms |
| title_fullStr | Deep-web search engine ranking algorithms |
| title_full_unstemmed | Deep-web search engine ranking algorithms |
| title_short | Deep-web search engine ranking algorithms |
| title_sort | deep web search engine ranking algorithms |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/61246 |
| work_keys_str_mv | AT wongbrianwaifung deepwebsearchenginerankingalgorithms |