On Concept Algebra for Computing with Words (CWW)

Computing with words (CWW) is an intelligent computing methodology for processing words, linguistic variables, and their semantics, which mimics the natural-language-based reasoning mechanisms of human beings in soft computing, semantic computing, and cognitive computing. The central objects in CWW techniques are words and linguistic variables, which may be formally modeled by abstract concepts that are a basic cognitive unit to identify and model a concrete entity in the real world and an abstract object in the perceived world. Therefore, concepts are the most fundamental linguistic entities that carries certain meanings in expression, thinking, reasoning, and system modeling, which may be formally modeled as an abstract and dynamic mathematical structure in denotational mathematics. This paper presents a formal theory for concept and knowledge manipulations in CWW known as concept algebra. The mathematical models of abstract and concrete concepts are developed based on the object-attribute-relation (OAR) theory. The formal methodology for manipulating knowledge as a concept network is described. Case studies demonstrate that concept algebra provides a generic and formal knowledge manipulation means, which is capable of dealing with complex knowledge and their algebraic operations in CWW.

[1]  Lotfi A. Zadeh,et al.  Some reflections on soft computing, granular computing and their roles in the conception, design and utilization of information/intelligent systems , 1998, Soft Comput..

[2]  Shushma Patel,et al.  A layered reference model of the brain (LRMB) , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[3]  Rudolf Wille,et al.  Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts , 2009, ICFCA.

[4]  Djelloul Ziadi,et al.  An Efficient Computation of the Equation K-automaton of a Regular K-expression , 2009, Fundam. Informaticae.

[5]  Yiyu Yao,et al.  On the System Algebra Foundations for Granular Computing , 2009, Int. J. Softw. Sci. Comput. Intell..

[6]  Lotfi A. Zadeh,et al.  Quantitative fuzzy semantics , 1971, Inf. Sci..

[7]  Yingxu Wang,et al.  The OAR Model of Neural Informatics for Internal Knowledge Representation in the Brain , 2007, Int. J. Cogn. Informatics Nat. Intell..

[8]  Ryszard S. Michalski,et al.  Categories and Concepts: Theoretical Views and Inductive Data Analysis , 1993 .

[9]  Yingxu Wang,et al.  On Cognitive Computing , 2009, Int. J. Softw. Sci. Comput. Intell..

[10]  D. Medin,et al.  Context and structure in conceptual combination , 1988, Cognitive Psychology.

[11]  M. Ross Quillian,et al.  4 – Semantic Memory , 1988 .

[12]  John R. Anderson A Spreading Activation Theory of Memory , 1988 .

[13]  Yingxu Wang,et al.  The Theoretical Framework of Cognitive Informatics , 2007, Int. J. Cogn. Informatics Nat. Intell..

[14]  Gregory L. Murphy,et al.  Theories and concept formation. , 1993 .

[15]  Lotfi A. Zadeh,et al.  From Computing with Numbers to Computing with Words - from Manipulation of Measurements to Manipulation of Perceptions , 2005, Logic, Thought and Action.

[16]  Lotfi A. Zadeh,et al.  A COMPUTATIONAL APPROACH TO FUZZY QUANTIFIERS IN NATURAL LANGUAGES , 1983 .

[17]  Yingxu Wang,et al.  On Concept Algebra: A Denotational Mathematical Structure for Knowledge and Software Modeling , 2008, Int. J. Cogn. Informatics Nat. Intell..

[18]  L. A. Zadeh,et al.  Fuzzy logic and approximate reasoning , 1975, Synthese.

[19]  J. Hampton Psychological representation of concepts. , 1997 .

[20]  Yingxu Wang,et al.  On Contemporary Denotational Mathematics for Computational Intelligence , 2008, Trans. Comput. Sci..

[21]  Rokia Missaoui,et al.  INCREMENTAL CONCEPT FORMATION ALGORITHMS BASED ON GALOIS (CONCEPT) LATTICES , 1995, Comput. Intell..

[22]  Yingxu Wang,et al.  On Abstract Intelligence: Toward a Unifying Theory of Natural, Artificial, Machinable, and Computational Intelligence , 2009, Int. J. Softw. Sci. Comput. Intell..

[23]  I. Burhan Turksen,et al.  A Foundation for Computing with Words: Meta-Linguistic Axioms , 2005 .

[24]  Witold Pedrycz,et al.  A Doctrine of Cognitive Informatics (CI) , 2009, Fundam. Informaticae.

[25]  Edward E. Smith,et al.  Categories and concepts , 1984 .

[26]  Yingxu Wang,et al.  Software Engineering Foundations: A Software Science Perspective , 2007 .

[27]  Yingxu Wang,et al.  A Knowledge Representation Tool for Autonomous Machine Learning Based on Concept Algebra , 2009, Trans. Comput. Sci..

[28]  Lotfi A. Zadeh,et al.  A fuzzy-algorithmic approach to the definition of complex or imprecise concepts , 1976 .

[29]  John R. Anderson Is human cognition adaptive? , 1991, Behavioral and Brain Sciences.

[30]  Allan Collins,et al.  A spreading-activation theory of semantic processing , 1975 .