Relaxing RDF queries based on user and domain preferences

Research in cooperative query answering is triggered by the observation that users are often not able to correctly formulate queries to databases such that they return the intended result. Due to lacking knowledge about the contents and the structure of a database, users will often only be able to provide very broad queries. Existing methods for automatically refining such queries based on user profiles often overshoot the target resulting in queries that do not return any answer. In this article, we investigate methods for automatically relaxing such over-constrained queries based on domain knowledge and user preferences. We describe a framework for information access that combines query refinement and relaxation in order to provide robust, personalized access to heterogeneous resource description framework data as well as an implementation in terms of rewriting rules and explain its application in the context of e-learning systems.

[1]  Werner Kießling,et al.  Preference SQL - Design, Implementation, Experiences , 2002, VLDB.

[2]  Alexandra Poulovassilis,et al.  A Relaxed Approach to RDF Querying , 2006, International Semantic Web Conference.

[3]  Peter Dolog,et al.  Personalizing access to learning networks , 2008, TOIT.

[4]  Domenico Beneventano,et al.  Description logics for semantic query optimization in object-oriented database systems , 2003, TODS.

[5]  Werner Kießling,et al.  Fixpoint iteration with subsumption in deductive databases , 1995, Journal of Intelligent Information Systems.

[6]  Amihai Motro FLEX: A Tolerant and Cooperative User Interface to Databases , 1990, IEEE Trans. Knowl. Data Eng..

[7]  Alexandra Poulovassilis,et al.  Event-Condition-Action Rule Languages for the Semantic Web , 2006, EDBT Workshops.

[8]  Alexandra Poulovassilis,et al.  Query Relaxation in RDF , 2008, J. Data Semant..

[9]  Stefano Ceri,et al.  A declarative approach to active databases , 1992, [1992] Eighth International Conference on Data Engineering.

[10]  Werner Kießling,et al.  Foundations of Preferences in Database Systems , 2002, VLDB.

[11]  Tobias Nipkow,et al.  Term rewriting and all that , 1998 .

[12]  Peter Dolog,et al.  Personalization in distributed e-learning environments , 2004, WWW Alt. '04.

[13]  Parke Godfrey,et al.  An overview of cooperative answering , 1992, Journal of Intelligent Information Systems.

[14]  Diana Maynard,et al.  REASE—The repository for learning units about the Semantic Web , 2007, New Rev. Hypermedia Multim..

[15]  Ronen I. Brafman,et al.  Reasoning With Conditional Ceteris Paribus Preference Statements , 1999, UAI.

[16]  Jan Chomicki,et al.  Preference formulas in relational queries , 2003, TODS.

[17]  M. Lacroix,et al.  Preferences; Putting More Knowledge into Queries , 1987, VLDB.

[18]  Alberto O. Mendelzon,et al.  Foundations of semantic web databases , 2004, PODS.

[19]  Peter Dolog,et al.  A Framework for Browsing, Manipulating and Maintaining Interoperable Learner Profiles , 2005, User Modeling.

[20]  Peter Dolog,et al.  Robust Query Processing for Personalized Information Access on the Semantic Web , 2006, FQAS.

[21]  Jan Brase,et al.  Usage of metadata , 2005 .

[22]  Parke Godfrey,et al.  Relaxation as a platform for cooperative answering , 1992, Journal of Intelligent Information Systems.

[23]  Frank van Harmelen,et al.  Exploring large document repositories with RDF technology: the DOPE project , 2004, IEEE Intelligent Systems.

[24]  Werner Kießling,et al.  Database Reasoning - A Deductive Framework for Solving Large and Complex Problems by Means of Subsumption , 1994, IS/KI.

[25]  Heiner Stuckenschmidt,et al.  Similarity-Based Query Caching , 2004, FQAS.

[26]  Nenad Stojanovic,et al.  On Analysing Query Ambiguity for Query Refinement: The Librarian Agent Approach , 2003, ER.

[27]  Arjohn Kampman,et al.  SeRQL: A Second Generation RDF Query Language , 2003 .