OntoCase - A Pattern-Based Ontology Construction Approach

As the technologies facilitating the Semantic Web become more and more mature they are also adopted by the business world. When developing semantic applications, constructing the underlying ontologies is a crucial part. Construction of enterprise ontologies need to be semi-automatic in order to reduce the effort required and the need for expert ontology engineers. Another important issue is to introduce knowledge reuse in the ontology construction process. By basing our semi-automatic method on the principles of case-based reasoning we envision a novel semi-automatic ontology construction process. The approach is based on automatic selection and application of patterns but also includes ontology evaluation and revision, as well as pattern candidate discovery. The development of OntoCase is still ongoing work, in this paper we report mainly on the initial realisation and first experiments concerning the retrieval and reuse phases.

[1]  Yorick Wilks,et al.  Background and Foreground Knowledge in Dynamic Ontology Construction: Viewing Text as Knowledge Maintenance , 2003 .

[2]  Yun Peng,et al.  Finding and Ranking Knowledge on the Semantic Web , 2005, SEMWEB.

[3]  Pradeep Ravikumar,et al.  A Comparison of String Distance Metrics for Name-Matching Tasks , 2003, IIWeb.

[4]  Simon C. K. Shiu,et al.  Foundations of Soft Case-Based Reasoning: Pal/Soft Case-Based Reasoning , 2004 .

[5]  Agnar Aamodt,et al.  CASE-BASED REASONING: FOUNDATIONAL ISSUES, METHODOLOGICAL VARIATIONS, AND SYSTEM APPROACHES AICOM - ARTIFICIAL INTELLIGENCE COMMUNICATIONS , 1994 .

[6]  Paola Velardi,et al.  Evaluation of OntoLearn, a Methodology for Automatic Learning of Domain Ontologies , 2005 .

[7]  Nicola Guarino,et al.  Formal Ontology and Information Systems , 1998 .

[8]  Sophia Ananiadou,et al.  The C-value/NC-value Method of Automatic Recognition for Multi-Word Terms , 1998, ECDL.

[9]  Yorick Wilks,et al.  An Incremental Tri-Partite Approach To Ontology Learning , 2006, LREC.

[10]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[11]  Martin Kavalec,et al.  A Study on Automated Relation Labelling in Ontology Learning , 2005 .

[12]  Kurt Sandkuhl,et al.  Ontology Construction in an Enterprise Context: Comparing and Evaluating Two Approaches , 2006, ICEIS.

[13]  Kevin D. Ashley,et al.  Textual case-based reasoning , 2005, Knowl. Eng. Rev..

[14]  Christiane Fellbaum,et al.  Book Reviews: WordNet: An Electronic Lexical Database , 1999, CL.

[15]  Eva Blomqvist.  Fully Automatic Construction of Enterprise Ontologies Using Design Patterns: Initial Method and First Experiences , 2005, OTM Conferences.

[16]  Michael Uschold,et al.  The Enterprise Ontology , 1998, The Knowledge Engineering Review.

[17]  York Sure-Vetter,et al.  Learning Disjointness , 2007, ESWC.

[18]  S. Pal,et al.  Foundations of Soft Case-Based Reasoning: Pal/Soft Case-Based Reasoning , 2004 .

[19]  Philipp Cimiano,et al.  Ontology Learning from Text: Methods, Evaluation and Applications , 2005 .

[20]  D. Mladení,et al.  SEMI-AUTOMATIC DATA-DRIVEN ONTOLOGY CONSTRUCTION SYSTEM , 2006 .

[21]  Harith Alani,et al.  Ontology ranking based on the analysis of concept structures , 2005, K-CAP '05.

[22]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[23]  Eva Blomqvist,et al.  Pattern ranking for semi-automatic ontology construction , 2008, SAC '08.

[24]  Jérôme Euzenat,et al.  A Survey of Schema-Based Matching Approaches , 2005, J. Data Semant..

[25]  Kurt Sandkuhl,et al.  Patterns in Ontology Engineering: Classification of Ontology Patterns , 2005, ICEIS.

[26]  Philipp Cimiano,et al.  Ontology learning and population from text - algorithms, evaluation and applications , 2006 .

[27]  Yun Peng,et al.  Swoogle: Searching for Knowledge on the Semantic Web , 2005, AAAI.

[28]  Aldo Gangemi,et al.  Ontology Design Patterns for Semantic Web Content , 2005, SEMWEB.