Component retrieval using knowledge-intensive conversational CBR

  • Authors:

  • Mingyang Gu;Ketil Bø

  • Affiliations:

  • Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway;Department of Computer and Information Science, Norwegian University of Science and Technology, Trondheim, Norway

  • Venue:
  • IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
  • Year:
  • 2006

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Abstract

One difficulty in software component retrieval comes from users’ incapability to well define their queries. In this paper, we propose a conversational component retrieval model (CCRM) to alleviate this difficulty. CCRM uses a knowledge-intensive conversational case-based reasoning method to help users to construct their queries incrementally through a mixed-initiative question-answering process. In this model, general domain knowledge is captured and utilized in helping tackle the following five tasks: feature inferencing, semantic similarity calculation, integrated question ranking, consistent question clustering and coherent question sequencing. This model is implemented, and evaluated in an image processing component retrieval application. The evaluation result gives us positive support.