Conference proceeding
A Term Association Approach for Genomics Information Retrieval
2011 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM 2011), pp 532-537
01 Jan 2011
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Modeling and mining term association is important for information retrieval, which allows an information retrieval system to retrieve relevant documents/passages more precisely. In this paper, we propose a new approach for discovering term associations among the keywords from a query. First, factor analysis is applied to discover some hidden common factors as the "eliteness" variables that can be used to estimate the importance of term associations. Second, a factor analysis based model and a corresponding algorithm are proposed. Then, we report experimental results that confirm the effectiveness and superiority of the proposed term association approach. Our approach achieves excellent results on the TREC 2007 and 2006 data sets, which provides a promising avenue for constructing high performance information retrieval systems.
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Details
- Title
- A Term Association Approach for Genomics Information Retrieval
- Creators
- Qinmin Hu - York Univ, Dept Comp Sci & Engn, Toronto, ON, CanadaJimmy Xiangji Huang - York Univ, Sch Informat Technol, Toronto, ON, CanadaXiaohua Hu - Drexel University
- Publication Details
- 2011 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM 2011), pp 532-537
- Series
- IEEE International Conference on Bioinformatics and Biomedicine-BIBM
- Publisher
- IEEE
- Number of pages
- 6
- Grant note
- Natural Sciences & Engineering Research Council (NSERC) of Canada; Natural Sciences and Engineering Research Council of Canada (NSERC) Early Researcher Award/Premier's Research Excellence Award
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000411330600098
- Scopus ID
- 2-s2.0-84862943616
- Other Identifier
- 991019167516404721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Mathematical & Computational Biology
- Medical Informatics