On Consensus Measures in Fuzzy Group Decision Making
MDAI '08 Sabadell Proceedings of the 5th International Conference on Modeling Decisions for Artificial Intelligence
Linguistic multiperson decision making based on the use of multiple preference relations
Fuzzy Sets and Systems
A recommender system for research resources based on fuzzy linguistic modeling
Expert Systems with Applications: An International Journal
A multi-disciplinar recommender system to advice research resources in University Digital Libraries
Expert Systems with Applications: An International Journal
IEEE Transactions on Fuzzy Systems
Computing with words in decision making: foundations, trends and prospects
Fuzzy Optimization and Decision Making
IEEE Transactions on Fuzzy Systems
A fuzzy MCDM approach for personnel selection
Expert Systems with Applications: An International Journal
Group decision making problems in a linguistic and dynamic context
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Maximum Bayesian entropy method for determining ordered weighted averaging operator weights
Computers and Industrial Engineering
Information Sciences: an International Journal
Ranking multi-attribute alternatives on the basis of linguistic labels in group decisions
Information Sciences: an International Journal
Determination of Ordered Weighted Averaging Operator Weights Based on the M-Entropy Measures
International Journal of Intelligent Systems
On weighted unbalanced linguistic aggregation operators in group decision making
Information Sciences: an International Journal
The optimal group consensus models for 2-tuple linguistic preference relations
Knowledge-Based Systems
A granular neural network: Performance analysis and application to re-granulation
International Journal of Approximate Reasoning
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Most information retrieval systems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express the weights of queries and the relevance degrees of documents. However, to improve the system–user interaction, it seems more adequate to express these linguistic weights and degrees by means of unbalanced linguistic scales, that is, linguistic term sets with different discrimination levels on both sides of the middle linguistic term. In this contribution we present an information retrieval system that accepts weighted queries whose weights are expressed using unbalanced linguistic term sets. Then, the system provides the retrieved documents classified in linguistic relevance classes assessed on unbalanced linguistic term sets. To do so, we propose a methodology to manage unbalanced linguistic information and we use the linguistic 2-tuple model as the representation base of the unbalanced linguistic information. Additionally, the linguistic 2-tuple model allows us to increase the number of relevance classes in the output and also to improve the performance of the information retrieval system. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 1197–1214, 2007.