IC-service: a service-oriented approach to the development of recommendation systems

Recommendation systems have proven to be useful in various application domains. However, current solutions are usually ad-hoc systems which are tightly-coupled with the application domain. We present the IC-Service, a recommendation service that can be included in any system in a loosely coupled way. The implementation follows the principles of service oriented computing and provides a solution to various problems arising in recommendation systems, e.g. to the problem of meta-recommendation systems development. Moreover, when properly configured, the IC-Service can be used by different applications (clients), and several independent instances of the IC-Service can collaborate to produce better recommendations. Service architecture and communication protocols are presented. The paper describes also ongoing work and applications based on the IC-Service.

[1]  T.V. Prabhakar,et al.  Dynamic selection of Web services with recommendation system , 2005, International Conference on Next Generation Web Services Practices (NWeSP'05).

[2]  Donald F. Ferguson,et al.  Toward a Programming Model for Service-Oriented Computing , 2005, ICSOC.

[3]  Enrico Blanzieri,et al.  Implicit Culture for Multi-agent Interaction Support , 2001, CoopIS.

[4]  Enrico Blanzieri,et al.  From actions to suggestions: supporting the work of biologists through laboratory notebooks , 2004 .

[5]  E. Michael Maximilien,et al.  A framework and ontology for dynamic Web services selection , 2004, IEEE Internet Computing.

[6]  Ramakrishnan Srikant,et al.  Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.

[7]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[8]  Alfons Kemper,et al.  Semantic Caching for Web Services , 2005, ICSOC.

[9]  John Riedl,et al.  E-Commerce Recommendation Applications , 2004, Data Mining and Knowledge Discovery.

[10]  K. Mullis,et al.  Specific enzymatic amplification of DNA in vitro: the polymerase chain reaction. , 1986, Cold Spring Harbor symposia on quantitative biology.

[11]  Greg Linden,et al.  Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .

[12]  Enrico Blanzieri,et al.  Implicit: an agent-based recommendation system for web search , 2005, AAMAS '05.

[13]  John Riedl,et al.  Meta-recommendation systems: user-controlled integration of diverse recommendations , 2002, CIKM '02.