Improving search quality of the Google search appliance
Author(s)Nguyen, Huy, M. Eng (Huy Le). Massachusetts Institute of Technology
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
David Elworthy and Regina Barzilay.
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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.
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (p. 69-73).
DepartmentMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.