Computing with WordsPaul P. Wang Wiley, 2001 M04 30 - 466 pages Fuzzy logic refers to a computer's ability to make decisions involving "grey" or "fuzzy" areas. As linguistics contains numerous "grey" areas, computing with words through the use of fuzzy logic is an extremely hot topic in database and Internet research. This book explores the state of the art in linguistic computation, discussing how current research findings are extending the application of fuzzy logic beyond control engineering and intelligent systems into the use of language on a computer. Fuzzy logic pioneer, Dr. Lofti Zadeh, provides the introduction for this thought-provoking work. |
From inside the book
Results 1-3 of 94
Page 82
... knowledge engineers and domain experts during the early stages of knowledge acquisition . A computer - generated expert system , especially in the form of if- then rules , can do a better job of inspiring an expert to make improvements ...
... knowledge engineers and domain experts during the early stages of knowledge acquisition . A computer - generated expert system , especially in the form of if- then rules , can do a better job of inspiring an expert to make improvements ...
Page 242
... knowledge in the language of predicate calculus . Nilsson's three theses are : 1. Knowledge of the environment . Intelligent machines will have knowledge of their environment . 2. Centrality of declarative knowledge . The most versatile ...
... knowledge in the language of predicate calculus . Nilsson's three theses are : 1. Knowledge of the environment . Intelligent machines will have knowledge of their environment . 2. Centrality of declarative knowledge . The most versatile ...
Page 278
... knowledge interact with an expert's ability to critique and modify computer - generated predictive models [ 9 ] . Although these systems are less robust than linear and neural models when deal- ing with noisy data , their perspicuity ...
... knowledge interact with an expert's ability to critique and modify computer - generated predictive models [ 9 ] . Although these systems are less robust than linear and neural models when deal- ing with noisy data , their perspicuity ...
Contents
MEYSTEL Department of Electrical and Computer Engineering | 1 |
FROM COMPUTING WITH NUMBERS TO COMPUTING WITH | 32 |
THE PROBLEMS | 69 |
Copyright | |
13 other sections not shown
Other editions - View all
Common terms and phrases
adverbs agents aggregation algorithms analysis applications approach artificial intelligence Bandler basic BK-products body systems Clinaid cognitive linguistic cognitive sciences complex computational semiotics computational verb computing with words concept constraint propagation context coreference crisp decision defined Definition domain dynamic entities environment example expressed extraction FDNF Figure formal front end fuzzy constraint fuzzy graph fuzzy information granulation fuzzy logic fuzzy relations Fuzzy Sets Syst grammar granularity human identified IEEE important inference input intelligent systems interpretation knowledge representation L. A. Zadeh L. J. Kohout labels language discourse linear linguistic terms linguistic variable mathematical meaning natural language processing neural objects operator perceptions performance phrase precision predicate principle problem Proc procedures propositions query reasoning relational computations relational structures represented rules SCIP Section semantic semiotic descriptors sentence specific syntactic texts theory tion truth tables ural language values WordNet