Bridging gaps between several frameworks for the idea of granulation

Two important ideas at the core of Zadeh's seminal contributions to fuzzy logic and approximate reasoning are the notions of granulation and of possibilistic uncertainty. In this paper, elaborating on the basis of some formal analogy, recently made by the authors, between possibility theory and formal concept analysis, we suggest other bridges between theories for which the concept of granulation is central. We highlight the common features between the notion of extensional fuzzy set with respect to a similarity relation and the notion of concept. We also discuss the case of fuzzy rough sets. Thus, we point out some fruitful cross-fertilizations between the possibilistic representation of information and several views of granulation emphasizing the idea of clusters of points that can be identified respectively on the basis of their closeness, or of their common labeling in terms of properties.

[1]  Didier Dubois,et al.  Possibility Theory and Formal Concept Analysis: Context Decomposition and Uncertainty Handling , 2010, IPMU.

[2]  Arie Tzvieli Possibility theory: An approach to computerized processing of uncertainty , 1990, J. Am. Soc. Inf. Sci..

[3]  Henri Prade,et al.  What are fuzzy rules and how to use them , 1996, Fuzzy Sets Syst..

[4]  Ivo Düntsch,et al.  Approximation Operators in Qualitative Data Analysis , 2003, Theory and Applications of Relational Structures as Knowledge Instruments.

[5]  Didier Dubois,et al.  The three semantics of fuzzy sets , 1997, Fuzzy Sets Syst..

[6]  Bernhard Ganter,et al.  Pattern Structures and Their Projections , 2001, ICCS.

[7]  Didier Dubois,et al.  A Possibility-Theoretic View of Formal Concept Analysis , 2007, Fundam. Informaticae.

[8]  Didier Dubois,et al.  Possibility Theory: Qualitative and Quantitative Aspects , 1998 .

[9]  Ivo Düntsch,et al.  MIXING MODAL AND SUFFICIENCY OPERATORS , 1999 .

[10]  Yiyu Yao,et al.  A Comparative Study of Formal Concept Analysis and Rough Set Theory in Data Analysis , 2004, Rough Sets and Current Trends in Computing.

[11]  L. Valverde On the structure of F-indistinguishability operators , 1985 .

[12]  Enrique H. Ruspini,et al.  On the semantics of fuzzy logic , 1991, Int. J. Approx. Reason..

[13]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[14]  Andrei Popescu,et al.  A general approach to fuzzy concepts , 2004, Math. Log. Q..

[15]  F. Klawonn Fuzzy points, fuzzy relations and fuzzy functions , 2000 .

[16]  Jürg Kohlas,et al.  Handbook of Defeasible Reasoning and Uncertainty Management Systems , 2000 .

[17]  Didier Dubois,et al.  Similarity versus Preference in Fuzzy Set-Based Logics , 1998 .

[18]  Mihir K. Chakraborty,et al.  On Fuzzy Sets and Rough Sets from the Perspective of Indiscernibility , 2011, ICLA.

[19]  R. Bellman,et al.  Abstraction and pattern classification , 1996 .

[20]  Bernhard Ganter,et al.  Formal Concept Analysis , 2013 .

[21]  Didier Dubois,et al.  Possibility theory and formal concept analysis: Characterizing independent sub-contexts , 2012, Fuzzy Sets Syst..

[22]  Didier Dubois,et al.  Possibility theory , 2018, Scholarpedia.

[23]  Anna Maria Radzikowska,et al.  A comparative study of fuzzy rough sets , 2002, Fuzzy Sets Syst..

[24]  Zainab Assaghir,et al.  A Possibility Theory-Oriented Discussion of Conceptual Pattern Structures , 2010, SUM.

[25]  Didier Dubois,et al.  Interpolation of fuzzy data: Analytical approach and overview , 2012, Fuzzy Sets Syst..

[26]  Lotfi A. Zadeh,et al.  Toward a generalized theory of uncertainty (GTU) - an outline , 2005, GrC.

[27]  L. Beran,et al.  [Formal concept analysis]. , 1996, Casopis lekaru ceskych.

[28]  Henri Prade,et al.  A logical approach to interpolation based on similarity relations , 1997, Int. J. Approx. Reason..

[29]  Andrei Popescu,et al.  Non-dual fuzzy connections , 2004, Arch. Math. Log..

[30]  Lotfi A. Zadeh,et al.  Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic , 1997, Fuzzy Sets Syst..

[31]  Francesc Esteva,et al.  Review of Triangular norms by E. P. Klement, R. Mesiar and E. Pap. Kluwer Academic Publishers , 2003 .

[32]  U. Höhle Quotients with respect to similarity relations , 1988 .

[33]  L. Godo,et al.  Logical approaches to fuzzy similarity-based reasoning: an overview , 2008 .

[34]  Michael Soltys Bulletin of the Section of Logic , 2002 .

[35]  Janusz Zalewski,et al.  Rough sets: Theoretical aspects of reasoning about data , 1996 .

[36]  Philippe Smets,et al.  Quantified Representation of Uncertainty and Imprecision , 1998 .

[37]  L. Zadeh Fuzzy sets as a basis for a theory of possibility , 1999 .

[38]  D. Dubois,et al.  Possibility theory as a basis for preference propagation in automated reasoning , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[39]  Didier Dubois,et al.  Possibility Theory and Formal Concept Analysis in Information Systems , 2009, IFSA/EUSFLAT Conf..

[40]  Yiyu Yao,et al.  Rough set approximations in formal concept analysis , 2004, IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04..

[41]  Henri Prade,et al.  A Parallel between Extended Formal Concept Analysis and Bipartite Graphs Analysis , 2010, IPMU.

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

[43]  D. Dubois,et al.  ROUGH FUZZY SETS AND FUZZY ROUGH SETS , 1990 .

[44]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[45]  Radim Belohlávek,et al.  Fuzzy Galois Connections , 1999, Math. Log. Q..

[46]  Lotfi A. Zadeh,et al.  Toward a generalized theory of uncertainty (GTU)--an outline , 2005, Inf. Sci..