Framework for Value Prediction of Knowledge-Based Applications

نویسندگان

  • Ali Imtiaz
  • Tobias Bürger
  • Igor O. Popov
  • Elena Paslaru Bontas Simperl
چکیده

Knowledge-based applications are characterized by their use of machine-understandable formalizations of expert knowledge. Complex knowledge structures, and the features which exploit them, can have a significant effect on the effort needed to develop such applications. Means to estimate this effort are, however, lacking. Furthermore, precise benefits of such applications, which are directly attributed to specific functionalities, remain unknown. In this paper we propose a preliminary Framework for Value Prediction whose intention is to study and to effectively predict the development effort as well as benefits of knowledge-based applications. The framework consists of five pillars which act as a road map to propose well-defined models. We furthermore discuss our initial experiences with using the framework to adapt existing software cost and benefit estimation models.

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تاریخ انتشار 2009