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Search Result Reranking Using Clustering
Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, Department of Computer and Information Science.
2011 (English)MasteroppgaveStudent thesis
Abstract [en]

Information Retrieval is a research area that has gained attention over the past two decades. Few of these researches have taken place in the biomed- ical domain where satisfying users’ information needs are relatively difficult to be met. The goal of this project is to find out if it is possible to use statistical methods in Biomedical Information Retrieval (IR) and improve retrieval performance, i.e. finding ways of fulfilling user information needs, in the biomedical domain using clustering with knowledge from the BioTracer project. K-Mean and Expectation Maximization (EM) approaches to clustering have been implemented in this project with more emphasis on the EM. Both ap- proaches are used to re-ranking users searched results in an attempt to find ways of fulfilling their information needs. Comparison between the Expec- tation Maximization and the K-mean are drawn in terms of their retrieval performance i.e. precision and recall, the performance of EM compared to ex- isting approaches to search results re-ranking using clustering and problems faced while implementing the EM.

Place, publisher, year, edition, pages
Institutt for datateknikk og informasjonsvitenskap , 2011. , 56 p.
Keyword [no]
ntnudaim:6087, MSINFOSYST Master in Information Systems, Information Systems
URN: urn:nbn:no:ntnu:diva-13634Local ID: ntnudaim:6087OAI: diva2:441333
Available from: 2011-09-15 Created: 2011-09-15

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