Adaptive Reactive Rich Internet Applications

Rich Internet Applications significantly raise the user experience compared with legacy page-based Web applications because of their highly responsive user interfaces. Although this is a tremendous advance, it does not solve the problem of the one-size-fits-all approach1 of current Web applications. So although Rich Internet Applications put the user in a position to interact seamlessly with the Web application, they do not adapt to the context in which the user is currently working. In this paper we address the on-the-fly personalization of Rich Internet Applications. We introduce the concept of ARRIAs: Adaptive Reactive Rich Internet Applications and elaborate on how they are able to adapt to the current working context the user is engaged in. An architecture for the ad hoc adaptation of Rich Internet Applications is presented as well as a holistic framework and tools for the realization of our on-the-fly personalization approach. We divided both the architecture and the framework into two levels: offline/design-time and online/run-time. For design-time we explain how to use ontologies in order to annotate Rich Internet Applications and how to use these annotations for conceptual Web usage mining. Furthermore, we describe how to create client-side executable rules from the semantic data mining results. We present our declarative lightweight rule language tailored to the needs of being executed directly on the client. Because of the event-driven nature of the user interfaces of Rich Internet Applications, we designed a lightweight rule language based on the event–condition–action paradigm.2 At run-time the interactions of a user are tracked directly on the client and in real-time a user model is built up. The user model then acts as input to and is evaluated by our client-side complex event processing and rule engine.

[1]  Narain H. Gehani,et al.  Event specification in an active object-oriented database , 1992, SIGMOD '92.

[2]  John A. Waterworth,et al.  A Pattern of Islands: Exploring Public Information Space in a Private Vehicle , 1994, MHVR.

[3]  Adrian Paschke,et al.  A Homogeneous Reaction Rule Language for Complex Event Processing , 2010, ArXiv.

[4]  Flavius Frasincar,et al.  Hypermedia Presentation Adaptation on the Semantic Web , 2002, AH.

[5]  Jesse James Garrett.  Ajax: A New Approach to Web Applications , 2007 .

[6]  Sharma Chakravarthy,et al.  Composite Events for Active Databases: Semantics, Contexts and Detection , 1994, VLDB.

[7]  L. Stein,et al.  OWL Web Ontology Language - Reference , 2004 .

[8]  Narain H. Gehani,et al.  COMPOSE: A System For Composite Specification And Detection , 1993, Advanced Database Systems.

[9]  Christoph G. Thomas.  BASAR: A Framework for Integrating Agents in the World Wide Web , 1995, Computer.

[10]  Steffen Staab,et al.  Semi-Automatic Engineering of Ontologies from Text , 2000, ICSE 2000.

[11]  Irene Garrigós,et al.  A Prototype Tool for the Automatic Generation of Adaptive Websites , 2007, AEWSE.

[12]  James R. Chen,et al.  User-Centered Indexing for Adaptive Information Access , 1996 .

[13]  Klaus R. Dittrich,et al.  Events in an Active Object-Oriented Database System , 1993, Rules in Database Systems.

[14]  Louis B. Rosenfeld,et al.  Information architecture for the world wide web - designing large-scale web sites (2. ed.) , 1998 .

[15]  Sharma Chakravarthy.  Sentinel: an object-oriented DBMS with event-based rules , 1997, SIGMOD '97.

[16]  Jakob Nielsen,et al.  Prioritizing Web Usability , 2006 .

[17]  Peter Dolog,et al.  The Personal Reader: Personalizing and Enriching Learning Resources Using Semantic Web Technologies , 2004, AH.

[18]  Peter Brusilovsky,et al.  Methods and techniques of adaptive hypermedia , 1996, User Modeling and User-Adapted Interaction.

[19]  Thorsten Joachims,et al.  WebWatcher : A Learning Apprentice for the World Wide Web , 1995 .

[20]  Bijan Parsia,et al.  Pellet: An OWL DL Reasoner , 2004, Description Logics.

[21]  Jun Ma,et al.  An Approach for Combining Ontology Learning and Semantic Tagging in the Ontology Development Process: eGovernment Use Case , 2007, WISE.

[22]  Boualem Benatallah.  Web Information Systems Engineering - WISE 2007, 8th International Conference on Web Information Systems Engineering, Nancy, France, December 3-7, 2007, Proceedings , 2007, WISE.

[23]  Anupriya Ankolekar,et al.  Rules for an Ontology-based Approach to Adaptation , 2006, 2006 First International Workshop on Semantic Media Adaptation and Personalization (SMAP'06).

[24]  Michael Mahemoff.  Ajax Design Patterns , 2006 .

[25]  Jaideep Srivastava,et al.  Automatic personalization based on Web usage mining , 2000, CACM.

[26]  Nenad Stojanovic,et al.  On Enriching Ajax with Semantics: The Web Personalization Use Case , 2007, ESWC.

[27]  Andreas Hotho,et al.  Semantic Web Mining: State of the art and future directions , 2006, J. Web Semant..

[28]  Vanda Broughton.  Essential Thesaurus Construction , 2006 .

[29]  Klaus R. Dittrich,et al.  Detecting composite events in active database systems using Petri nets , 1994, Proceedings of IEEE International Workshop on Research Issues in Data Engineering: Active Databases Systems.

[30]  Myra Spiliopoulou,et al.  A Framework for the Evaluation of Session Reconstruction Heuristics in Web-Usage Analysis , 2003, INFORMS J. Comput..

[31]  James Chen,et al.  Adaptive hypertext navigation based on user goals and context , 1993, User Modeling and User-Adapted Interaction.

[32]  Steffen Staab,et al.  Mining Ontologies from Text , 2000, EKAW.

[33]  Harold Boley,et al.  The Rule Markup Language: RDF-XML Data Model, XML Schema Hierarchy, and XSL Transformations , 2001, INAP.

[34]  Sharma Chakravarthy,et al.  SnoopIB: Interval-based event specification and detection for active databases , 2003, Data Knowl. Eng..

[35]  Roland Stühmer,et al.  From Business Rules to Application Rules in Rich Internet Applications , 2008, Scalable Comput. Pract. Exp..

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

[37]  Murray Silverstein,et al.  A Pattern Language , 1977 .

[38]  Bamshad Mobasher,et al.  Using Ontologies to Discover Domain-Level Web Usage Profiles , 2002 .

[39]  Dunja Mladenic,et al.  A Roadmap for Web Mining: From Web to Semantic Web , 2003, EWMF.

[40]  Giovanni Toffetti Carughi,et al.  Modeling Distributed Events in Data-Intensive Rich Internet Applications , 2007, WISE.

[41]  Jenifer Tidwell.  Designing Interfaces , 2005 .