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Computing with words for Discovery Investing

2012 IEEE International Conference on Fuzzy Systems, 2012
This paper presents a case study of what we believe to be the first commercial product to use interval type-2 fuzzy logic in a computing with words application to the digital economy. The Discovery Investing Scoreboard is a free online service for evaluating the investment potential of companies in a manner distinct from more traditional styles of ...
John T. Rickard   +5 more
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Conceptual Spaces and Computing with Words

2015
The purpose of this paper is to explore synergies and gaps in research in Conceptual Spaces (CS) and Computing with Words (CWW), which both attempt to address aspects of human cognition such as judgement and intuition. Both CS and CWW model concepts in term of collections of properties, and use similarity as a key computational device.
Aisbett, Janet   +2 more
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Computing with Granular Words

2011
Computational linguistics is a sub-field of artificial intelligence; it is an interdisciplinary field dealing with statistical and/or rule-based modeling of natural language from a computational perspective. Traditionally, fuzzy logic is used to deal with fuzziness among single linguistic terms in documents.
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“Computing with Words”-Based Concept Retrieval

2019
Concept retrieval aims to extract documents that are semantically similar to the query. In view of the communication gap between the user and the system at the interface level in keyword-based search systems, user input in Natural Language (NL) is preferable.
Bushra Siddique, M. M. Sufyan Beg
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Data compactification and computing with words

Engineering Applications of Artificial Intelligence, 2010
The underlying objective of this study is to show how fuzzy sets (and information granules in general) and grammatical inference play an interdependent role in information granularization and knowledge-based problem characterization. The bottom-up organization of the material starts with a concept and selected techniques of data compactification which ...
Witold Pedrycz, Stuart H. Rubin
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Computing with descriptive and veristic words

18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397), 2003
Computing with words [Zadeh, 1995] is fundamental to our understanding the foundation of fuzzy theory. Naturally, there are a large variety of "words" that we need to recognize and utilize in our computational paradigms. However, descriptive and veristic words are essential for the fundamental derivation of fuzzy set and logic formulas.
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Computations with words

In fact, computing with words is a method in which the objects are words, and the computations are propositions extracted from ordinary conversation. For example, small, large, far, and heavy, not very likely, the price of gas in Iran is low and increasing a lot.
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Fuzzy Logic = Computing with Words

2019
In seinem Artikel „Fuzzy Logic = Computing with Words“ stellte Zadeh erstmals sein Konzept des Rechnens vor. Im Folgenden sollen nun die Grundelemente von Computing with Words erlautert werden. Dazu gehen wir von den folgenden Leitfragen aus: Was bedeutet Rechnen mit Worten? Was ist ein Fuzzy Set? Wie kann man damit rechnen?
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Computing with words in formal methods

International Journal of Intelligent Systems, 2000
Summary: Formal methods are used to improve the quality of complex computer software by means of documenting system specifications in a precise and structured manner, the most popular specification language for formal methods is \(Z\). However, based on classical set theory and classical logic, this mathematical language can only deal effectively with ...
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Computing with Words: Zadeh, Turing, Popper and Occam

IEEE Computational Intelligence Magazine, 2007
In this article, after explaining Zadeh's computing with words (CWW) paradigm, I argue that for this paradigm to be embraced, it must be validated using a Turinglike test, use a scientifically correct fuzzy set model for words, namely interval type-2 fuzzy sets (IT2 FSs), and be simple, meaning that fuzzy set operations should be as simple as possible.
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