Data models for retrieving task-specific and technicians-adaptive hypermedia

  • Authors:
  • Ammar M. Huneiti

  • Affiliations:
  • Computer Information Systems Department, Jordan University, Amman, Jordan

  • Venue:
  • WSEAS Transactions on Computers
  • Year:
  • 2008

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Abstract

This paper introduces a set of data models for facilitating the retrieval of task-specific and user-adaptive hypermedia documents concerning product fault diagnosis. These models include an integrated fault data model, a stereotype user model, and a semantic product data model. Moreover, the paper outlines the benefits of employing adaptive hypermedia to support the performance of technicians specifically for product fault diagnosis. The suggested stereotype user model represents the knowledge of the technician regarding the performed task. This user model is then used for the adaptive retrieval of finely separated and semantically classified product information elements. A detailed example of how task-specific and user-centred hypermedia can assist in synchronizing the output of a product diagnostic expert system with the product technical documentation is introduced. A general architecture for the suggested adaptive hypermedia system is outlined. The data models proposed in this paper are demonstrated through a prototype adaptive expert system for locating and correcting braking system faults in a forklift truck.