Parametric Extension of the Most Preferred OWA Operator and Its Application in Search Engine's Rank
Author(s) -
Xiuzhi Sang,
Xinwang Liu
Publication year - 2013
Publication title -
journal of applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.307
H-Index - 43
eISSN - 1687-0042
pISSN - 1110-757X
DOI - 10.1155/2013/273758
Subject(s) - operator (biology) , ranking (information retrieval) , parametric statistics , preference , rank (graph theory) , context (archaeology) , extension (predicate logic) , mathematical optimization , computer science , grasp , mathematics , artificial intelligence , statistics , combinatorics , paleontology , biochemistry , chemistry , repressor , biology , transcription factor , gene , programming language
Most preferred ordered weighted average (MP-OWA) operator is a new kind of neat (dynamic weight) OWA operator in the aggregation operator families. It considers the preferences of all alternatives across the criteria and provides unique aggregation characteristics in decision making. In this paper, we propose the parametric form of the MP-OWA operator to deal with the uncertainty preference information, which includes MP-OWA operator as its special case, and it also includes the most commonly used maximum, minimum, and average aggregation operators. A special form of parametric MP-OWA operator with power function is proposed. Some properties of the parametric MP-OWA operator are provided and the advantages of them in decision making problems are summarized. The new proposed parametric MP-OWA operator can grasp the subtle preference information of the decision maker according to the application context through multiple aggregation results. They are applied to rank search engines considering the relevance of the retrieved queries. An search engine ranking example illustrates the application of parametric MP-OWA operator in various decision situations
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