Automated case creation and management for diagnostic CBR systems

摘要

With the rapid development of case-based reasoning (CBR) techniques such as case retrieval and case adaptation, CBR has been widely applied to various real-world applications. A successful case-based reasoning system requires a high-quality case base, which provides rich and efficient solutions for solving real-world problems. How to automatically create and manage such a case base is a vital but unsolved problem. This paper tackles this important problem. We proposed a methodology for creating cases from readily available large-sized databases, which were collected in the routine operations. Building on techniques from case-based reasoning and natural language processing, we present a methodology for automatically creating cases at initial stage of a CBR system development. After the detailed description of the methodology, we introduce a case study for validating the usefulness of the methodology. The experimental results show that the proposed methodology significantly reduces the human effort required for authoring cases, and we are able to automatically create the high-quality cases for diagnostic CBR systems from historic maintenance and operational data at the initial stage of system development.