A Framework for the Retrieval of Multimedia Objects Based on Four-Valued Fuzzy Description Logics

Knowledge representation, in particular logic, combined together with database and information retrieval techniques may play an important role in the development of so-called intelligent multimedia retrieval systems. In this paper we will present a logic-based framework in which multimedia objects’ medium dependent properties (objects’ low level features) and multimedia objects’ medium independent properties (abstract objects’ features, or objects’ semantics) are addressed in a principled way. The framework is logic-based as it relies on the use of a four-valued fuzzy Description Logics for (i) representing the semantics of multimedia objects and (ii) for defining the retrieval process in terms of logical entailment. Low level features are not represented explicitly within the logic, but may be addressed by means of procedural attachments over a concrete domain. Description Logics are object-oriented representation formalisms capturing the most popular features of structured representation of knowledge. They are a good compromise between computational complexity and expressive power and, thus, may be seen as a promising tool within the context of logic-based multimedia information retrieval.

[1]  Constantin Virgil Negoita,et al.  On fuzziness in information retrieval , 1976 .

[2]  Nuel D. Belnap,et al.  A Useful Four-Valued Logic , 1977 .

[3]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .

[4]  Hector J. Levesque,et al.  A Logic of Implicit and Explicit Belief , 1984, AAAI.

[5]  Jean H. Gallier,et al.  Logic for Computer Science: Foundations of Automatic Theorem Proving , 1985 .

[6]  Etienne Kerre,et al.  The use of fuzzy set theory in information retrieval and databases: A survey , 1986, J. Am. Soc. Inf. Sci..

[7]  Peter F. Patel-Schneider,et al.  A Four-Valued Semantics for Terminological Logics , 1989, Artif. Intell..

[8]  Premkumar T. Devanbu,et al.  LaSSIE: a knowledge-based software information system , 1990, [1990] Proceedings. 12th International Conference on Software Engineering.

[9]  Udo Pletat,et al.  The LILOG knowledge representation system , 1991, SGAR.

[10]  Gloria Bordogna,et al.  Query term weights as constraints in fuzzy information retrieval , 1991, Inf. Process. Manag..

[11]  Gert Smolka,et al.  Attributive Concept Descriptions with Complements , 1991, Artif. Intell..

[12]  Werner Nutt,et al.  Tractable Concept Languages , 1991, IJCAI.

[13]  Franz Baader,et al.  A Scheme for Integrating Concrete Domains into Concept Languages , 1991, IJCAI.

[14]  Diane J. Litman,et al.  Terminological Reasoning with Constraint Networks and an Application to Plan Recognition , 1992, KR.

[15]  Shamkant B. Navathe,et al.  Knowledge mining by imprecise querying: a classification-based approach , 1992, [1992] Eighth International Conference on Data Engineering.

[16]  D. Kraft,et al.  Fuzzy Sets and Generalized Boolean Retrieval Systems , 1983, Int. J. Man Mach. Stud..

[17]  Francesco M. Donini,et al.  Decidable reasoning in terminological knowledge representation systems , 1993 .

[18]  Francesco M. Donini,et al.  Decidable Reasoning in Terminological Knowledge Representation Systems , 1993, IJCAI.

[19]  Fabrizio Sebastiani,et al.  A probabilistic terminological logic for modelling information retrieval , 1994, SIGIR '94.

[20]  Serge Abiteboul,et al.  Foundations of Databases , 1994 .

[21]  Ronald R. Yager,et al.  Fuzzy Sets as a Tool for Modeling , 1995, Computer Science Today.

[22]  Umberto Straccia,et al.  A relevance terminological logic for information retrieval , 1996, SIGIR '96.

[23]  Vito F. Sinisi,et al.  Entailment: The Logic of Relevance and Necessity , 1996 .

[24]  Carole A. Goble,et al.  Describing and classifying multimedia using the description logic GRAIL , 1996, Electronic Imaging.

[25]  Sukhamay Kundu,et al.  A Sound and Complete Fuzzy Logic System Using Zadeh's Implication Operator , 1996, ISMIS.

[26]  Patrick Lambrix,et al.  Learning Composite Concepts in Description Logics: A First Step , 1996, ISMIS.

[27]  Alon Y. Halevy,et al.  Recursive Plans for Information Gathering , 1997, IJCAI.

[28]  Umberto Straccia A Four-Valued Fuzzy Propositional Logic , 1997, IJCAI.

[29]  Umberto Straccia,et al.  A Sequent Calculus for Reasoning in Four-Valued Description Logics , 1997, TABLEAUX.

[30]  Umberto Straccia,et al.  Modelling the Retrieval of Structured Documents Containing Texts and Images , 1997, ECDL.

[31]  Umberto Straccia,et al.  Mirlog: A Logic for Multimedia Information Retrieval , 1998 .

[32]  Umberto Straccia,et al.  A Fuzzy Description Logic , 1998, AAAI/IAAI.

[33]  Craig A. Knoblock,et al.  Modeling Web Sources for Information Integration , 1998, AAAI/IAAI.

[34]  Ricky K. Taira,et al.  Knowledge-Based Image Retrieval with Spatial and Temporal Constructs , 1998, IEEE Trans. Knowl. Data Eng..

[35]  Christopher A. Welty DLs for DLs: Description Logics for Digital Libraries , 1998, Description Logics.

[36]  Andreas Zeller,et al.  Versioning System Models Through Description Logic , 1998, SCM.

[37]  Arif Ghafoor,et al.  Semantic Modeling and Knowledge Representation in Multimedia Databases , 1999, IEEE Trans. Knowl. Data Eng..