Probability-based fusion of information retrieval result sets

被引:0
|
作者
D. Lillis
F. Toolan
A. Mur
L. Peng
R. Collier
J. Dunnion
机构
[1] University College Dublin,School of Computer Science and Informatics
来源
Artificial Intelligence Review | 2006年 / 25卷
关键词
Data fusion; Information retrieval;
D O I
暂无
中图分类号
学科分类号
摘要
Information Retrieval (IR) forms the basis of many information management tasks. Information management itself has become an extremely important area as the amount of electronically available information increases dramatically. There are numerous methods of performing the IR task both by utilising different techniques and through using different representations of the information available to us. It has been shown that some algorithms outperform others on certain tasks. Combining the results produced by different algorithms has resulted in superior retrieval performance and this has become an important research area. This paper introduces a probability-based fusion technique probFuse that shows initial promise in addressing this question. It also compares probFuse with the common CombMNZ data fusion technique.
引用
收藏
页码:179 / 191
页数:12
相关论文
共 50 条
  • [11] A geometric framework for data fusion in information retrieval
    Wu, Shengli
    Crestani, Fabio
    INFORMATION SYSTEMS, 2015, 50 : 20 - 35
  • [12] Research of Information Retrieval Method Based on Fuzzy Rough Sets Theory
    Tan, Dekun
    Sun, Hui
    Deng, Minjun
    2008 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, VOLS 1 AND 2, 2008, : 576 - +
  • [13] A geometric probabilistic framework for data fusion in information retrieval
    Wu, Shengli
    2007 PROCEEDINGS OF THE 10TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4, 2007, : 24 - 31
  • [14] Predictive models for the effectiveness of data fusion in information retrieval
    Ng, KB
    NATIONAL ONLINE MEETING, PROCEEDINGS 2000, 2000, : 291 - 302
  • [15] Applying statistical principles to data fusion in information retrieval
    Wu, Shengli
    EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (02) : 2997 - 3006
  • [16] A probability-based unified framework for semantic search and recommendation
    Lee, Jae-won
    Kim, Han-joon
    Lee, Sang-goo
    JOURNAL OF INFORMATION SCIENCE, 2013, 39 (05) : 608 - 628
  • [17] Fusion of information retrieval engines (FIRE)
    Mounir, SA
    Goharian, N
    Mahoney, M
    Salem, A
    Frieder, O
    INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED PROCESSING TECHNIQUES AND APPLICATIONS, VOLS I-IV, PROCEEDINGS, 1998, : 1718 - 1725
  • [18] Enhancing Information Retrieval Process Using Data Fusion by ABC Weighted Based Fuzzy Retrieval in Health Care Analytic Software
    Gomathi, B.
    Sakthivel, P.
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2016, 6 (03) : 863 - 868
  • [19] Automatic ranking of information retrieval systems using data fusion
    Nuray, R
    Can, F
    INFORMATION PROCESSING & MANAGEMENT, 2006, 42 (03) : 595 - 614
  • [20] Information Retrieval Based on Decompositions of Rough Sets Referring to Fuzzy Tolerance Relations
    Wu, Chen
    Dai, Jun
    INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY, 2009, 9 (03): : 270 - 272