Extracting complex linguistic data summaries from personnel database via simple linguistic aggregations

Authors:
Zheng Pei;Yang Xu;Da Ruan;Keyun Qin
Affiliations:
School of Mathematics and Computer Engineering, Xihua University, Chengdu, Sichuan 610039, China;Department of Mathematics, Southwest Jiaotong University, Chengdu, Sichuan 610031, China;Belgian Nuclear Research Centre (SCKCEN), Boeretang 200, B-2400 Mol, Ghent University, Gent, Belgium;Department of Mathematics, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
Venue:
Information Sciences: an International Journal
Year:
2009

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Abstract

A linguistic data summary of a given data set is desirable and human consistent for any personnel department. To extract complex linguistic data summaries, the LOWA operator is used from fuzzy logic and some numerical examples are also provided in this paper. To obtain a complex linguistic data summary with a higher truth degree, genetic algorithms are applied to optimize the number and membership functions of linguistic terms and to select a part of truth degrees for aggregations, in which linguistic terms are represented by the 2-tuple linguistic representation model.