Improving Query Term Expansion With Machine Learning

Wood, Vaughn

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Improving Query Term Expansion With Machine Learning

Wood, Vaughn

Cite this item: Wood, V. (2013). Improving Query Term Expansion With Machine Learning (Thesis, Master of Science). University of Otago. Retrieved from http://hdl.handle.net/10523/3791

Permanent link to OUR Archive version: http://hdl.handle.net/10523/3791

Date: 2013

Advisor: Trotman, Andrew

Degree Name: Master of Science

Degree Discipline: Computer Science

Publisher: University of Otago

Keywords: Information Retrieval; Search; Search Engines; Machine Learning; Genetic Algorithms

Research Type: Thesis

Languages: English

Abstract:

Vocabulary mismatch is an impediment to responding to user queries with relevant results. Stemmers solve this problem by conflating terms with similar spellings. In this thesis we use machine learning to create a stemmer optimised for Information Retrieval performance. We investigate further improvement to stemmers with corpus information. With the goal of stemming selectively for further performance gains we investigate the prediction of query performance.

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