Adaptive Information Analysis in Higher Education Institutes

Information integration plays an important role in academic environments since it provides a comprehensive view of education data and enables mangers to analyze and evaluate the effectiveness of education processes. However, the problem in the traditional information integration is the lack of personalization due to weak information resource or unavailability of analysis functionality. In this research the layered service-oriented framework was proposed which augmented recommendation approaches with components of semantic based integration to provide adaptive, flexible, and context based information integration and analysis for decision makers in Higher Education Institutes. This framework encompassed the integration of structured information from internal data sources as well as unstructured data from the Web. The main objective of this paper was to adapt the content as well as appropriate services for personalized information analysis. In addition, the framework could enable administrators to analyze instances of education information and receive recommendation of new information sources as well as web services based on the current education status. Service orientation paradigm provides adaptive, flexible, and scalable means of communication for service interoperability and interaction among the framework components. Semantic web technologies help to overcome the heterogeneity among information sources and facilitate on-demand web service discovery and invocation for efficient information analysis.