The problem of linguistic approximation in clinical decision making
International Journal of Approximate Reasoning
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Benchmarking in linguistic importance weighted aggregations
Fuzzy Sets and Systems
Computing with words in intelligent database querying: standalone and internet-based application
Information Sciences—Informatics and Computer Science: An International Journal - Special issue computing with words
Information Sciences: an International Journal
Computing with words in decision making: foundations, trends and prospects
Fuzzy Optimization and Decision Making
Intelligent systems for decision support
Intelligent systems for decision support
IEEE Transactions on Fuzzy Systems
Perceptual reasoning for perceptual computing: a similarity-based approach
IEEE Transactions on Fuzzy Systems
Computing with words for hierarchical decision making applied to evaluating a weapon system
IEEE Transactions on Fuzzy Systems - Special section on computing with words
Perceptual Computing: Aiding People in Making Subjective Judgments
Perceptual Computing: Aiding People in Making Subjective Judgments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
A 2-tuple fuzzy linguistic representation model for computing with words
IEEE Transactions on Fuzzy Systems
A formal model of computing with words
IEEE Transactions on Fuzzy Systems
Computing with words via Turing machines: a formal approach
IEEE Transactions on Fuzzy Systems
A new version of 2-tuple fuzzy linguistic representation model for computing with words
IEEE Transactions on Fuzzy Systems
Aggregation Using the Linguistic Weighted Average and Interval Type-2 Fuzzy Sets
IEEE Transactions on Fuzzy Systems
Aggregation Using the Fuzzy Weighted Average as Computed by the Karnik–Mendel Algorithms
IEEE Transactions on Fuzzy Systems
A Fuzzy Linguistic Methodology to Deal With Unbalanced Linguistic Term Sets
IEEE Transactions on Fuzzy Systems
Encoding Words Into Interval Type-2 Fuzzy Sets Using an Interval Approach
IEEE Transactions on Fuzzy Systems
Corrections to “Aggregation Using the Linguistic Weighted Average and Interval Type-2 Fuzzy Sets”
IEEE Transactions on Fuzzy Systems
Information Sciences: an International Journal
Novel Weighted Averages versus Normalized Sums in Computing with Words
Information Sciences: an International Journal
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The Word decoder is a very important approach for decoding in the Perceptual Computer. It maps the computing with words (CWWs) engine output, which is a fuzzy set, into a word in a codebook so that it can be understood. However, the Word decoder suffers from significant information loss, i.e., the fuzzy set model of the mapped word may be quite different from the fuzzy set output by the CWW engine, especially when the codebook is small. In this paper we propose a Reconstruction decoder, which represents the CWW engine output as a combination of two successive codebook words with minimum information loss by solving a constrained optimization problem. The Reconstruction decoder preserves the shape information of the CWW engine output in a simple form without sacrificing much accuracy. It can be viewed as a generalized Word decoder and is also implicitly a Rank decoder. Moreover, it is equivalent to the 2-tuple representation under certain conditions. The effectiveness of the Reconstruction decoder is verified by three experiments.