article

Construction of weak and strong similarity measures for ordered sets of documents using fuzzy set techniques

Authors:

C. MichelAuthors Info & Claims

Information Processing and Management: an International Journal, Volume 39, Issue 5

Pages 771 - 807

https://doi.org/10.1016/S0306-4573(02)00027-4

Published: 01 September 2003 Publication History

Abstract

Ordered sets of documents are encountered more and more in information distribution systems, such as information retrieval systems. Classical similarity measures for ordinary sets of documents hence need to be extended to these ordered sets. This is done in this paper using fuzzy set techniques. First a general similarity measure is developed which contains the classical strong similarity measures such as Jaccard, Dice, Cosine and which contains the classical weak similarity measures such as Recall and Precision.Then these measures are extended to comparing fuzzy sets of documents. Measuring the similarity for ordered sets of documents is a special case of this, where, the higher the rank of a document, the lower its weight is in the fuzzy set. Concrete forms of these similarity measures are presented. All these measures are new and the ones for the weak similarity measures are the first of this kind (other strong similarity measures have been given in a previous paper by Egghe and Michel).Some of these measures are then tested in the IR-system Profil-Doc. The engine SPIRIT^© extracts ranked documents sets in three different contexts, each for 600 request. The practical useability of the OS-measures is then discussed based on these experiments.

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Digital Library

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Egghe, L., & Michel, C. (2002). Strong similarity measures for ordered sets of documents in information retrieval. Information Processing and Management, 38(6), 823-848.

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Cited By

Khajavi RArastoopoor S(2023)Semantic domain comparison of research keywords by indicator-based fuzzy distancesInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10346860:5Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.ipm.2023.103468
Wang TChiang H(2011)Solving multi-label text categorization problem using support vector machine approach with membership functionNeurocomputing10.1016/j.neucom.2011.07.00174:17(3682-3689)Online publication date: 1-Oct-2011
https://dl.acm.org/doi/10.1016/j.neucom.2011.07.001
Mylonas PVallet DCastells PFernÁndez MAvrithis Y(2008)Personalized information retrieval based on context and ontological knowledgeThe Knowledge Engineering Review10.1017/S026988890700128223:1(73-100)Online publication date: 1-Mar-2008
https://dl.acm.org/doi/10.1017/S0269888907001282
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Index Terms

Construction of weak and strong similarity measures for ordered sets of documents using fuzzy set techniques
1. Information systems
  1. Information retrieval
    1. Document representation

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cover image Information Processing and Management: an International Journal

Information Processing and Management: an International Journal Volume 39, Issue 5

September 2003

137 pages

ISSN:0306-4573

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Pergamon Press, Inc.

United States

Publication History

Published: 01 September 2003

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Cited By

Khajavi RArastoopoor S(2023)Semantic domain comparison of research keywords by indicator-based fuzzy distancesInformation Processing and Management: an International Journal10.1016/j.ipm.2023.10346860:5Online publication date: 1-Sep-2023
https://dl.acm.org/doi/10.1016/j.ipm.2023.103468
Wang TChiang H(2011)Solving multi-label text categorization problem using support vector machine approach with membership functionNeurocomputing10.1016/j.neucom.2011.07.00174:17(3682-3689)Online publication date: 1-Oct-2011
https://dl.acm.org/doi/10.1016/j.neucom.2011.07.001
Mylonas PVallet DCastells PFernÁndez MAvrithis Y(2008)Personalized information retrieval based on context and ontological knowledgeThe Knowledge Engineering Review10.1017/S026988890700128223:1(73-100)Online publication date: 1-Mar-2008
https://dl.acm.org/doi/10.1017/S0269888907001282
Pieczyńska ADrapała J(2006)Neural network approach for learning of the world structure by cognitive agentsProceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III10.1007/11893011_128(1012-1019)Online publication date: 9-Oct-2006
https://dl.acm.org/doi/10.1007/11893011_128
Pieczyńska A(2006)Flexible method for a distance measure between communicative agents’ stored perceptionsProceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II10.1007/11893004_29(227-234)Online publication date: 9-Oct-2006
https://dl.acm.org/doi/10.1007/11893004_29

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