Data Dependencies in Codd's Relational Model with Similarities

This chapter deals with data dependencies in Codd’s relational model of data. In particular, we deal with fuzzy logic extensions of the relational model which consist in adding similarity relations to domains and consider functional dependencies in these extensions. We present a particular extension and functional dependencies in this extension which follows the principles of fuzzy logic in narrow sense. We present selected features and results regarding this extension. Then, we use this extension as a reference model and compare it to several other extensions proposed in the literature. We argue that following the principles of fuzzy logic in narrow sense the same way as following the principles of classical logic in case of ordinary Codd’s relational model helps achieve transparency, versatility, conceptual clarity, and theoretical and computational tractability of the extension. We outline several topics for future research.

[1]  José Galindo,et al.  Fuzzy Databases: Modeling, Design, and Implementation , 2006 .

[2]  Petr Hájek,et al.  Metamathematics of Fuzzy Logic , 1998, Trends in Logic.

[3]  Walid G. Aref,et al.  Supporting top-kjoin queries in relational databases , 2004, The VLDB Journal.

[4]  Olga Pons,et al.  GEFRED: A Generalized Model of Fuzzy Relational Databases , 1994, Inf. Sci..

[5]  Wen Gao,et al.  Content-Based Video Semantic Analysis , 2009, Semantic Mining Technologies for Multimedia Databases.

[6]  Daniel Maier,et al.  Customer Investigation Process at Credit Suisse , 2009, Database Technologies: Concepts, Methodologies, Tools, and Applications.

[7]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[8]  Heikki Mannila,et al.  Algorithms for Inferring Functional Dependencies from Relations , 1994, Data Knowl. Eng..

[9]  Bernhard Ganter,et al.  Formal Concept Analysis: Mathematical Foundations , 1998 .

[10]  Patrick Bosc,et al.  Fuzzy databases : principles and applications , 1996 .

[11]  Juan C. Cubero,et al.  A new definition of fuzzy functional dependency in fuzzy relational databases , 1994, Int. J. Intell. Syst..

[12]  Weiyi Liu,et al.  Fuzzy data dependencies and implication of fuzzy data dependencies , 1997, Fuzzy Sets Syst..

[13]  Yoshikane Takahashi Fuzzy Database Query Languages and Their Relational Completeness Theorem , 1993, IEEE Trans. Knowl. Data Eng..

[14]  B. Buckles,et al.  A fuzzy representation of data for relational databases , 1982 .

[15]  Vilém Vychodil,et al.  Attribute Implications in a Fuzzy Setting , 2006, ICFCA.

[16]  Vilém Vychodil,et al.  Relational Model of Data over Domains with Similarities: An Extension for Similarity Queries and Knowledge Extraction , 2006, 2006 IEEE International Conference on Information Reuse & Integration.

[17]  Giangiacomo Gerla,et al.  Fuzzy Logic: Mathematical Tools for Approximate Reasoning , 2001 .

[18]  Xuelong Li,et al.  Semantic Mining Technologies for Multimedia Databases , 2009 .

[19]  Vilém Vychodil,et al.  Fuzzy attribute logic over complete residuated lattices , 2006, J. Exp. Theor. Artif. Intell..

[20]  Masao Mukaidono,et al.  Fuzzy Conditional Probability Relations and their Applications in Fuzzy Information Systems , 2004, Knowledge and Information Systems.

[21]  Arun K. Majumdar,et al.  Fuzzy Functional Dependencies and Lossless Join Decomposition of Fuzzy Relational Database Systems , 1988, ACM Trans. Database Syst..

[22]  W. W. Armstrong,et al.  Dependency Structures of Data Base Relationships , 1974, IFIP Congress.

[23]  Sumit Sarkar,et al.  A probabilistic relational model and algebra , 1996, TODS.

[24]  Wilma Penzo,et al.  Rewriting rules to permeate complex similarity and fuzzy queries within a relational database system , 2005, IEEE Transactions on Knowledge and Data Engineering.

[25]  Norbert Fuhr,et al.  A probabilistic relational algebra for the integration of information retrieval and database systems , 1997, TOIS.

[26]  Guoqing Chen,et al.  Efficient discovery of functional dependencies with degrees of satisfaction , 2004, Int. J. Intell. Syst..

[27]  Etienne E. Kerre,et al.  A computational algorithm for the FFD transitive closure and a complete axiomatization of fuzzy functional dependence (FFD) , 1994, Int. J. Intell. Syst..

[28]  B. Buckles,et al.  A domain calculus for fuzzy relational databases , 1989 .

[29]  B. Bhuniya,et al.  Lossless Join Property in Fuzzy Relational Databases , 1993, Data Knowl. Eng..

[30]  David Maier,et al.  The Theory of Relational Databases , 1983 .

[31]  Henri Prade,et al.  Fuzzy relational databases: Representational issues and reduction using similarity measures , 1987 .

[32]  Siegfried Gottwald,et al.  Fuzzy Sets and Fuzzy Logic , 1993 .

[33]  Tzung-Pei Hong,et al.  Mining functional dependencies from fuzzy relational databases , 2000, SAC '00.

[34]  Jennifer Widom,et al.  The Lowell database research self-assessment , 2003, CACM.

[35]  Zongmin Ma,et al.  Intelligent Databases: Technologies and Applications , 2006 .

[36]  Sadok Ben Yahia,et al.  An Extension of Classical Functional Dependency: Dynamic Fuzzy Functional Dependency , 1999, Inf. Sci..

[37]  Henri Prade,et al.  Generalizing Database Relational Algebra for the Treatment of Incomplete/Uncertain Information and Vague Queries , 1984, Inf. Sci..

[38]  Ronald Fagin,et al.  Combining fuzzy information: an overview , 2002, SGMD.

[39]  Vilém Vychodil,et al.  Codd's Relational Model of Data and Fuzzy Logic: Comparisons, Observations, and Some New Results , 2006, 2006 International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (CIMCA'06).

[40]  Vilém Vychodil,et al.  Data Tables with Similarity Relations: Functional Dependencies, Complete Rules and Non-redundant Bases , 2006, DASFAA.

[41]  Petr Hájek,et al.  On very true , 2001, Fuzzy Sets Syst..

[42]  R. Belohlávek Fuzzy Relational Systems: Foundations and Principles , 2002 .

[43]  ˇ RadimB Pavelka-style fuzzy logic for attribute implications , 2006 .

[44]  Ronald Fagin,et al.  Combining Fuzzy Information from Multiple Systems , 1999, J. Comput. Syst. Sci..

[45]  Ajantha Dahanayake,et al.  Agile Development Methods and Component-Orientation: A Review and Analysis , 2004, Advanced Topics in Database Research, Vol. 3.

[46]  Didier Dubois,et al.  Fuzzy functional dependencies-an overview and a critical discussion , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[47]  Vincent Duquenne,et al.  Familles minimales d'implications informatives résultant d'un tableau de données binaires , 1986 .

[48]  John S. Erickson Database Technologies: Concepts, Methodologies, Tools, and Applications (4 Volumes) , 2009, Database Technologies: Concepts, Methodologies, Tools, and Applications.

[49]  Sujeet Shenoi,et al.  Functional dependencies and normal forms in the fuzzy relational database model , 1992, Inf. Sci..

[50]  Satoko Titani,et al.  Globalization of intui tionistic set theory , 1987, Ann. Pure Appl. Log..

[51]  Jeffrey D. Ullman,et al.  Principles Of Database And Knowledge-Base Systems , 1979 .

[52]  D. K. Gupta,et al.  Fuzzy inclusion dependencies in fuzzy relational databases , 2004, International Conference on Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004..

[53]  V. Novák,et al.  Mathematical Principles of Fuzzy Logic , 1999 .

[54]  Vilém Vychodil,et al.  Functional Dependencies of Data Tables Over Domains with Similarity Relations , 2005, IICAI.

[55]  Kevin Chen-Chuan Chang,et al.  RankSQL: query algebra and optimization for relational top-k queries , 2005, SIGMOD '05.

[56]  Aidan R. Vining,et al.  Adoption, Improvement, and Disruption: Predicting the Impact of Open Source Applications in Enterprise Software Markets , 2008, J. Database Manag..

[57]  Devendra K. Tayal,et al.  A complete axiomatization of fuzzy functional dependencies using fuzzy function , 2005, Fuzzy Sets Syst..