Improving search quality of the Google search appliance
Name
518049865-MIT.pdf
Description
Full printable version
Size
8.78 MB
Format
Adobe PDF
Checksum (MD5)
35034ed7c4d0608ed0e1ea509a1669a7
Author(s)
Nguyen, Huy, M. Eng (Huy Le). Massachusetts Institute of Technology
Advisor(s)
David Elworthy and Regina Barzilay.
Date Issued
2009
Publisher
Massachusetts Institute of Technology
Abstract
In this thesis, we describe various experiments on the ranking function of the Google Search Appliance to improve search quality. An evolutionary computation framework is implemented and applied to optimize various parameter settings of the ranking function. We evaluate the importance of IDF in the ranking function and achieve small improvements in performance. We also examine many ways to combining the query-independent and query-dependent scores. Lastly, we perform various experiments with signals based on the positions of the query terms in the document.
Description
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.
Includes bibliographical references (p. 69-73).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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