Social Network Database Querying Based on Computing with Words

Fuzzy relationships and their role in modeling weighted social relational networks are discussed. We describe how the idea of computing with words can provide a bridge between a network analyst’s linguistic description of social network concepts and the formal model of the network. We then turn to some examples of taking an analyst’s network concepts and formally representing them in terms of network properties. We first do this for the concept of clique and then for the idea of node importance. Finally we introduce the idea of vector–valued nodes and begin developing a technology of social network database theory.

[1]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[2]  Ronald R. Yager,et al.  Level sets and the extension principle for interval valued fuzzy sets and its application to uncertainty measures , 2008, Inf. Sci..

[3]  D. Knoke.  Understanding Social Networks: Theories, Concepts, and Findings , 2013 .

[4]  T. Pavlidis,et al.  Fuzzy sets and their applications to cognitive and decision processes , 1977 .

[5]  José L. Verdegay,et al.  On Valuation and Optimization Problems in Fuzzy Graphs: A General Approach and Some Particular Cases , 1990, INFORMS J. Comput..

[6]  Azriel Rosenfeld,et al.  FUZZY GRAPHS††The support of the Office of Computing Activities, National Science Foundation, under Grant GJ-32258X, is gratefully acknowledged, as is the help of Shelly Rowe in preparing this paper. , 1975 .

[7]  R. Yager.  Quantifier guided aggregation using OWA operators , 1996, Int. J. Intell. Syst..

[8]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[9]  Witold Pedrycz,et al.  Granular computing: an introduction , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[10]  C. Prell.  Social Network Analysis: History, Theory and Methodology , 2011 .

[11]  Robert A. Meyers,et al.  Encyclopedia of Complexity and Systems Science , 2009 .

[12]  Alex Meystel,et al.  CHAPTER 1 – Outline of a Computational Theory of Perceptions Based on Computing with Words , 2000 .

[13]  Michel Grabisch,et al.  Fuzzy Measures and Integrals , 1995 .

[14]  Charu C. Aggarwal,et al.  Social Network Data Analytics , 2011 .

[15]  Lotfi A. Zadeh,et al.  The concept of a linguistic variable and its application to approximate reasoning-III , 1975, Inf. Sci..

[16]  Guy De Tré,et al.  An Overview of Fuzzy Approaches to Flexible Database Querying , 2009, Database Technologies: Concepts, Methodologies, Tools, and Applications.

[17]  Ronald R. Yager,et al.  Intelligent social network analysis using granular computing , 2008, Int. J. Intell. Syst..

[18]  Mark Newman,et al.  Networks: An Introduction , 2010 .

[19]  Lotfi A. Zadeh,et al.  Fuzzy Logic , 2009, Encyclopedia of Complexity and Systems Science.

[20]  M. Sugeno.  FUZZY MEASURES AND FUZZY INTEGRALS—A SURVEY , 1993 .

[21]  Lotfi A. Zadeh,et al.  Fuzzy logic = computing with words , 1996, IEEE Trans. Fuzzy Syst..

[22]  Ronald R. Yager,et al.  Human Behavioral Modeling Using Fuzzy and Dempster–Shafer Theory , 2008 .

[23]  Lotfi A. Zadeh,et al.  Generalized theory of uncertainty (GTU) - principal concepts and ideas , 2006, Comput. Stat. Data Anal..

[24]  Lotfi A. Zadeh,et al.  Similarity relations and fuzzy orderings , 1971, Inf. Sci..

[25]  Tom A. B. Snijders,et al.  Social Network Analysis , 2011, International Encyclopedia of Statistical Science.

[26]  Huan Liu,et al.  Social Computing, Behavioral Modeling, and Prediction , 2008 .

[27]  L. Kóczy.  Fuzzy graphs in the evaluation and optimization of networks , 1992 .

[28]  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.