NDLI: Exploring statistical attributes obtained from fuzzy agreement models

Content Provider	IEEE Xplore Digital Library
Author	Miller, S. Wagner, C. Garibaldi, J.M.
Copyright Year	2014
Description	Author affiliation: Horizon Digital Econ. Res. Sch. of Comput. Sci., Univ. of Nottingham, Nottingham, UK (Miller, S.; Wagner, C.; Garibaldi, J.M.)
Abstract	In this paper we explore the characteristics of Type-1 Fuzzy Set agreement models based on interval data through contrasting statistical measures of the fuzzy models and the raw data respectively. We create Type-1 Fuzzy Set models using the Interval Agreement Approach, and then extract a preliminary set of attributes that encapsulate aspects of the agreement models. In order to explore what these attributes can tell us, we compare them with a set of traditional statistical measures of consensus which are applied to the raw data. Two interval-valued survey data sets are employed in this study, a synthetic data set consisting of 30 groups of 10 experts rating 25 objects which is used to provide a large example, and a real-world data set consisting of 7 groups of 4-8 cyber-security experts rating 26 security components that was collected during a decision making exercise at GCHQ, Cheltenham, UK. We show that while there are areas in which traditional methods and the attributes extracted from the Type-1 Fuzzy Set agreement models overlap, there are also attributes that do not appear to be replicated, suggesting that these attributes contain additional information about the consensus within the groups. A discussion of the results is provided, along with the conclusions that can be drawn and considerations for future work on this subject.
Starting Page	792
Ending Page	799
File Size	1905824
Page Count	8
File Format	PDF
e-ISBN	9781479920723
DOI	10.1109/FUZZ-IEEE.2014.6891817
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Xenon Data structures Boolean functions Conferences Fuzzy systems Optimized production technology Ground penetrating radar Type-1 Fuzzy Sets Survey Data Correlation Coefficients Interval Agreement Approach Agreement Modelling Computing With Words
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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