Representation and reasoning of context-dependant knowledge in distributed fuzzy ontologies

Most of current knowledge based systems manage impressive amounts of information (especially distributed fuzzy information). In addition to widely pointed-out integration and maintenance difficulties, other common problem is overwhelming of users with much more information than the strictly necessary for fulfilling a task. This issue has been pointed out with the name of ''information overload''. Use of context knowledge has been envisioned as an appropriate solution to deal with this information overload matter. In this paper, we present a distributed fuzzy context-domain relevance (DFCDR) model for representation in fuzzy ontologies relevance relations between fuzzy context ontology and distributed fuzzy domain ontologies. In fact, the DFCDR model is a distributed fuzzy extension of the context-domain relevance (CDR) model.

[1]  Siu Cheung Hui,et al.  Automatic fuzzy ontology generation for semantic Web , 2006, IEEE Transactions on Knowledge and Data Engineering.

[2]  Boris Motik,et al.  OWL 2: The next step for OWL , 2008, J. Web Semant..

[3]  Xijin Tang,et al.  Using ontology to improve precision of terminology extraction from documents , 2009, Expert Syst. Appl..

[4]  Boris Motik,et al.  Managing multiple and distributed ontologies on the Semantic Web , 2003, The VLDB Journal.

[5]  G. Stamou,et al.  Reasoning with Very Expressive Fuzzy Description Logics , 2007, J. Artif. Intell. Res..

[6]  Bernhard Hollunder.  An alternative proof method for possibilistic logic and its application to terminological logics , 1994, Int. J. Approx. Reason..

[7]  Carsten Lutz,et al.  E-connections of abstract description systems , 2004, Artif. Intell..

[8]  Jae Yeol Lee,et al.  Visualization and interaction of pervasive services using context-aware augmented reality , 2008, Expert Syst. Appl..

[9]  Thomas Lukasiewicz,et al.  Expressive probabilistic description logics , 2008, Artif. Intell..

[10]  Anind K. Dey,et al.  Understanding and Using Context , 2001, Personal and Ubiquitous Computing.

[11]  Fernando Ortega.  Managing vagueness in ontologies , 2011 .

[12]  James H. Aylor,et al.  Computer for the 21st Century , 1999, Computer.

[13]  Ohbyung Kwon.  A social network approach to resolving group-level conflict in context-aware services , 2009, Expert Syst. Appl..

[14]  Dieter Fensel,et al.  Ontologies: A silver bullet for knowledge management and electronic commerce , 2002 .

[15]  Ian Horrocks,et al.  From SHIQ and RDF to OWL: the making of a Web Ontology Language , 2003, J. Web Semant..

[16]  Umberto Straccia,et al.  Transforming Fuzzy Description Logics into Classical Description Logics , 2004, JELIA.

[17]  Baowen Xu,et al.  A Distributed and Fuzzy Extension of Description Logics , 2006, KES.

[18]  Umberto Straccia,et al.  fuzzyDL: An expressive fuzzy description logic reasoner , 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

[19]  Umberto Straccia,et al.  Fuzzy description logics under Gödel semantics , 2009, Int. J. Approx. Reason..

[20]  Ian Horrocks,et al.  The Even More Irresistible SROIQ , 2006, KR.

[21]  Umberto Straccia,et al.  Reasoning within Fuzzy Description Logics , 2011, J. Artif. Intell. Res..

[22]  Fausto Giunchiglia,et al.  Local Models Semantics, or Contextual Reasoning = Locality + Compatibility , 1998, KR.

[23]  Ju Wang,et al.  Reasoning within expressive fuzzy rough description logics , 2009, Fuzzy Sets and Systems.

[24]  Luciano Serafini,et al.  Distributed Description Logics: Assimilating Information from Peer Sources , 2003, J. Data Semant..

[25]  Stefanos D. Kollias,et al.  Uncertainty and the Semantic Web , 2006, IEEE Intelligent Systems.

[26]  Euiho Suh,et al.  Context-aware system for proactive personalized service based on context history , 2009, Expert Syst. Appl..

[27]  Fernando Bobillo,et al.  Representation of context-dependant knowledge in ontologies: A model and an application , 2008, Expert Syst. Appl..

[28]  Umberto Straccia,et al.  A fuzzy description logic for the semantic web , 2006, Fuzzy Logic and the Semantic Web.

[29]  Keith Cheverst,et al.  UTILIZING CONTEXT HISTORY TO PROVIDE DYNAMIC ADAPTATIONS , 2004, Appl. Artif. Intell..

[30]  Jia Zhang,et al.  A JESS-enabled context elicitation system for providing context-aware Web services , 2008, Expert Syst. Appl..

[31]  Ian Horrocks,et al.  Ontologies and the semantic web , 2008, CACM.

[32]  Alexander Borgida,et al.  Aspects of Distributed and Modular Ontology Reasoning , 2005, IJCAI.

[33]  Dieter Fensel,et al.  Knowledge Engineering: Principles and Methods , 1998, Data Knowl. Eng..

[34]  Claudia Linnhoff-Popien,et al.  A Context Modeling Survey , 2004 .

[35]  Siu Cheung Hui,et al.  Automatic fuzzy ontology generation for semantic help-desk support , 2006, IEEE Transactions on Industrial Informatics.

[36]  Harry Chen,et al.  The SOUPA Ontology for Pervasive Computing , 2005 .

[37]  Diego Calvanese,et al.  The description logic handbook: theory , 2003 .

[38]  Monique Calisti,et al.  Whitestein Series in Software Agent Technologies , 2005 .

[39]  Umberto Straccia,et al.  Managing uncertainty and vagueness in description logics for the Semantic Web , 2008, J. Web Semant..

[40]  Euiho Suh,et al.  Packet-based context aware system to determine information system user's context , 2008, Expert Syst. Appl..

[41]  Suqin Tang,et al.  Reasoning with rough description logics: An approximate concepts approach , 2008, Information Sciences.

[42]  Kyong Joo Oh,et al.  Context-aware mobile service for routing the fastest subway path , 2009, Expert Syst. Appl..

[43]  Bijan Parsia,et al.  Ontology-Enabled Pervasive Computing Applications , 2003, IEEE Intell. Syst..

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

[45]  Roy H. Campbell,et al.  Use of Ontologies in Pervasive Computing Environments , 2003 .

[46]  Ali F. Farhoomand,et al.  Managerial information overload , 2002, CACM.

[47]  Dazhou Kang,et al.  Reasoning Problems on Distributed Fuzzy Ontologies , 2008, RSKT.

[48]  Mahadev Satyanarayanan,et al.  Pervasive computing: vision and challenges , 2001, IEEE Wirel. Commun..

[49]  Mark Weiser,et al.  The computer for the 21st Century , 1991, IEEE Pervasive Computing.

[50]  Diego Calvanese,et al.  The Description Logic Handbook , 2007 .

[51]  Xiaohui Hu,et al.  A novel intelligent service selection algorithm and application for ubiquitous web services environment , 2009, Expert Syst. Appl..

[52]  Jihoon Kim,et al.  Concept lattices for visualizing and generating user profiles for context-aware service recommendations , 2009, Expert Syst. Appl..

[53]  G Stix,et al.  The mice that warred. , 2001, Scientific American.

[54]  Euiho Suh,et al.  Context-aware systems: A literature review and classification , 2009, Expert Syst. Appl..

[55]  Frank van Harmelen,et al.  Contextualizing ontologies , 2004, J. Web Semant..

[56]  Hashim Habiballa.  Resolution Strategies for Fuzzy Description Logic , 2007, EUSFLAT Conf..

[57]  Ju Wang,et al.  Reasoning within intuitionistic fuzzy rough description logics , 2009, Inf. Sci..

[58]  Ah-Hwee Tan,et al.  Modelling situation awareness for Context-aware Decision Support , 2009, Expert Syst. Appl..

[59]  Bijan Parsia,et al.  Combining OWL ontologies using epsilon-Connections , 2006, J. Web Semant..

[60]  Letizia Tanca,et al.  A methodology for a Very Small Data Base design , 2007, Inf. Syst..

[61]  Fernando Bobillo,et al.  DeLorean: A Reasoner for Fuzzy OWL 1.1 , 2008, URSW.

[62]  James A. Hendler,et al.  The Semantic Web" in Scientific American , 2001 .