Improving search quality of the Google search appliance

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.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2009

Author dc:creator

• Nguyen, Huy, M. Eng (Huy Le). Massachusetts Institute of Technology

Advisor dc:contributor.advisor

• David Elworthy and Regina Barzilay.

• Electrical Engineering and Computer Science.

Statement dc:rights

• 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/53174

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/53174