Ontology-Based User Context Management: The Challenges of Imperfection and Time-Dependence

Robust and scalable user context management is the key enabler for the emerging context- and situation-aware applications, and ontology-based approaches have shown their usefulness for capturing especially context information on a high level of abstraction But so far the problem has not been approached as a data management problem, which is key to scalability and robustness The specific challenges lie in the imperfection of high-level context information, its time-dependence and the variability in the dynamics between its different elements The approach presented in this paper presents a layered data model which structures the problems and is geared towards flexible and efficient query processing in combination of relational database and logic-based techniques The techniques have been successfully applied for context-aware corporate learning support.

[1]  Terry Winograd,et al.  Architectures for Context , 2001, Hum. Comput. Interact..

[2]  Danyel Fisher,et al.  Using egocentric networks to understand communication , 2005, IEEE Internet Computing.

[3]  Amihai Motro,et al.  Management of uncertainty in database systems , 1995 .

[4]  Dominik Heckmann A specialized representation for ubiquitous computing and user modeling , 2003 .

[5]  Peter Brusilovsky,et al.  User Modeling 2003 , 2003, Lecture Notes in Computer Science.

[6]  Ian Horrocks,et al.  OWL-QL - a language for deductive query answering on the Semantic Web , 2004, J. Web Semant..

[7]  Claudia Linnhoff-Popien,et al.  CoOL: A Context Ontology Language to Enable Contextual Interoperability , 2003, DAIS.

[8]  Eric Horvitz,et al.  The Lumière Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users , 1998, UAI.

[9]  Peter Dolog,et al.  Challenges and Benefits of the Semantic Web for User Modelling , 2003 .

[10]  Andreas Schmidt,et al.  User Context Aware Delivery of E-Learning Material: Approach and Architecture , 2004, J. Univers. Comput. Sci..

[11]  Nigel Davies,et al.  UbiComp 2004: Ubiquitous Computing , 2004, Lecture Notes in Computer Science.

[12]  Andreas Abecker,et al.  Context-Aware, Proactive Delivery of Task-Specific Information: The KnowMore Project , 2000, Inf. Syst. Frontiers.

[13]  Jadwiga Indulska,et al.  A software engineering framework for context-aware pervasive computing , 2004, Second IEEE Annual Conference on Pervasive Computing and Communications, 2004. Proceedings of the.

[14]  Johann-Christoph Freytag,et al.  Query Processing Using Ontologies , 2005, CAiSE.

[15]  Boris Motik,et al.  Reducing {$\mathcal SHIQ^-$} Description Logic to Disjunctive Datalog Programs , 2004, KR 2004.

[16]  Tao Gu,et al.  Ontology based context modeling and reasoning using OWL , 2004, IEEE Annual Conference on Pervasive Computing and Communications Workshops, 2004. Proceedings of the Second.

[17]  Jadwiga Indulska,et al.  Modelling and using imperfect context information , 2004, IEEE Annual Conference on Pervasive Computing and Communications Workshops, 2004. Proceedings of the Second.

[18]  Uwe Hansmann,et al.  Pervasive Computing , 2003 .

[19]  Laks V. S. Lakshmanan,et al.  ProbView: a flexible probabilistic database system , 1997, TODS.

[20]  Boris Motik,et al.  Reasoning in Description Logics with a Concrete Domain in the Framework of Resolution , 2004, ECAI.

[21]  Smith Barry,et al.  Learning – Teaching – Knowledge – Adaptivity (LLWA), University of Karlsruhe (2003). , 2003 .

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

[23]  Robert B. Ross,et al.  Probabilistic temporal databases, I: algebra , 2001, TODS.

[24]  Mounia Lalmas,et al.  Using Dempster-Shafer's Theory of Evidence to Combine Aspects of Information Use , 2004, Journal of Intelligent Information Systems.

[25]  Peter Steenkiste,et al.  Providing contextual information to ubiquitous computing applica-tions , 2002 .

[26]  Amihai Motro,et al.  Sources of Uncertainty, Imprecision, and Inconsistency in Information Systems , 1996, Uncertainty Management in Information Systems.

[27]  Andreas Schmidt A Layered Model for User Context Management with Controlled Aging and Imperfection Handling , 2005, MRC@IJCAI.

[28]  Antonio Krüger,et al.  A User Modeling Markup Language (UserML) for Ubiquitous Computing , 2003, User Modeling.

[29]  Peter Steenkiste,et al.  Providing contextual information to pervasive computing applications , 2003, Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, 2003. (PerCom 2003)..

[30]  Douglas B. Terry,et al.  Continuous queries over append-only databases , 1992, SIGMOD '92.

[31]  Amihai Motro,et al.  Uncertainty Management in Information Systems: From Needs to Solution , 1996 .

[32]  Simon Parsons,et al.  Addendum to "Current Approaches to Handling Imperfect Information in Data and Knowledge Bases" , 1996, IEEE Trans. Knowl. Data Eng..

[33]  Hector Garcia-Molina,et al.  The Management of Probabilistic Data , 1992, IEEE Trans. Knowl. Data Eng..

[34]  Jennifer Widom,et al.  Continuous queries over data streams , 2001, SGMD.

[35]  Klaus-Dieter Althoff,et al.  Professional Knowledge Management, Third Biennial Conference, WM 2005, Kaiserslautern, Germany, April 10-13, 2005, Revised Selected Papers , 2005, Wissensmanagement.

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

[37]  Curtis E. Dyreson,et al.  Supporting valid-time indeterminacy , 1998, TODS.

[38]  Carsten Lutz,et al.  Description Logics with Concrete Domains-A Survey , 2002, Advances in Modal Logic.

[39]  Agnès Voisard,et al.  Context- and Situation-Awareness in Information Logistics , 2004, EDBT Workshops.

[40]  Axel Küpper,et al.  Quality of Context: What It Is And Why We Need It , 2004 .

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

[42]  Jadwiga Indulska,et al.  Modeling Context Information in Pervasive Computing Systems , 2002, Pervasive.

[43]  H. V. Jagadish,et al.  ProTDB: Probabilistic Data in XML , 2002, VLDB.

[44]  Norbert Fuhr,et al.  pDAML+OIL: a probabilistic extension to DAML+OIL based on probabilistic Datalog , 2004 .

[45]  Boris Motik,et al.  Reducing SHIQ-Description Logic to Disjunctive Datalog Programs , 2004, KR.

[46]  Dominik Heckmann,et al.  Ubiquitous user modeling , 2006 .

[47]  V. S. Subrahmanian,et al.  PXML: a probabilistic semistructured data model and algebra , 2003, Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405).

[48]  Andreas Schmidt,et al.  XI3 - Towards an Integration Web , 2002 .

[49]  Wolfgang Lindner,et al.  Current Trends in Database Technology - EDBT 2004 Workshops, EDBT 2004 Workshops PhD, DataX, PIM, P2P&DB, and ClustWeb, Heraklion, Crete, Greece, March 14-18, 2004, Revised Selected Papers , 2004, EDBT Workshops.

[50]  Sjaak Brinkkemper,et al.  Information Systems Engineering: State of the Art and Research Themes , 2000 .

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

[52]  Andreas Schmidt,et al.  Bridging the Gap between Knowledge Management and E-Learning with Context-Aware Corporate Learning , 2005, Wissensmanagement.

[53]  Andreas Schmidt Potentials and Challenges of Context-Awareness for Learning Solutions , 2005, LWA.

[54]  Andreas Schmidt Context-steered learning: the learning in process approach , 2004, IEEE International Conference on Advanced Learning Technologies, 2004. Proceedings..

[55]  Michael Pittarelli,et al.  The Theory of Probabilistic Databases , 1987, VLDB.

[56]  Barry Smith,et al.  A user profiling component with the aid of user ontologies , 2003 .