Service configuration knowledge representation, acquisition and reasoning

To appropriately meet increasingly diverse customer needs, services are committed to certain configuration in a paradigm similar with product mass customization. This paper presents a hybrid approach based on ontologies and rules to achieve representing, acquiring and reasoning service configuration knowledge. Structural knowledge is represented by ontology and formalized by OWL, resulting in well-defined semantics. Rule knowledge is represented in SWRL, a rule language based on OWL. In addition, rule knowledge is aquired by LCNN and rulex. Finally, knowledge reasoning is carried out based on the JESS rule engine.

[1]  Shensheng Zhang,et al.  An interactive service customization model , 2006, Inf. Softw. Technol..

[2]  Cheng Hsu,et al.  Engineering service products: the case of mass-customising service agreements for heavy equipment industry , 2006, Int. J. Serv. Technol. Manag..

[3]  Joachim Diederich,et al.  Survey and critique of techniques for extracting rules from trained artificial neural networks , 1995, Knowl. Based Syst..

[4]  W. Massberg,et al.  Life Cycle-Based Service Design for Innovative Business Models , 2004 .

[5]  Yiwen Sun,et al.  Configuration of product extension services in servitisation using an ontology-based approach , 2012 .

[6]  Robert Winter,et al.  Mass Customization and Beyond — Evolution of Customer Centricity in Financial Services , 2002 .

[7]  Daniel Sabin,et al.  Product Configuration Frameworks - A Survey , 1998, IEEE Intell. Syst..

[8]  H. Lan,et al.  SWRL : A semantic Web rule language combining OWL and ruleML , 2004 .

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

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

[11]  Michael Uschold,et al.  Ontologies: principles, methods and applications , 1996, The Knowledge Engineering Review.

[12]  Jaap Gordijn,et al.  Energy Services: A Case Study in Real-World Service Configuration , 2004, CAiSE.

[13]  Juha Tiihonen,et al.  A conceptual model for configurable services , 2005 .

[14]  Eleutherios Papathanassiou,et al.  Mass customisation: management approaches and internet opportunities in the financial sector in the UK , 2004, Int. J. Inf. Manag..

[15]  Ralf Knackstedt,et al.  Configurative Service Engineering - A Rule-Based Configuration Approach for Versatile Service Processes in Corrective Maintenance , 2009 .

[16]  Jaap Gordijn,et al.  Value Webs: using ontologies to bundle real-world services , 2004, IEEE Intelligent Systems.

[17]  Shlomo Geva,et al.  Local cluster neural net: Architecture, training and applications , 1998, Neurocomputing.