A fuzzy linguistic IRS model based on a 2-tuple fuzzy linguistic approach

被引：57
|
作者：
Herrera-Viedma, E. [1 ]
Lopez-Herrera, A. G.
Luque, M.
Porcel, C.
机构：
[1] Univ Granada, Dept Comp Sci & AI, Granada, Spain
[2] Univ Jaen, Dept Comp Sci, Jaen, Spain
[3] Univ Cordoba, Dept Comp Sci & NA, Cordoba, Spain
来源：
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS | 2007年 / 15卷 / 02期
关键词：
information retrieval; fuzzy linguistic modelling; weighted queries;
D O I：
10.1142/S0218488507004534
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Information Retrieval Systems (IRSs) based on an ordinal fuzzy linguistic approach present some problems of loss of information and lack of precision when working with discrete linguistic expression domains or when applying approximation operations in the symbolic aggregation methods. In this paper, we present a new IRS model based on the 2-tuple fuzzy linguistic approach, which allows us to overcome the problems of ordinal fuzzy linguistic IRSs and improve their performance.
引用
收藏
页码：225 / 250
页数：26
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