Collaborative Case Retrieval within the Implicit Culture Framework

The retrieval of cases plays important role in CBR systems. Current solutions to the problem of case retrieval adopt various similarity metrics such as utility-based, adaptation-guided similarity, and collaborative retrieval. In this paper, we present a collaborative architecture for case retrieval, where users share their experience in using cases and interact with one another by means of software agents. Past experiences are used to improve case retrieval. We describe a system for choosing software patterns as an implementation of the proposed architecture. Experimental results show that the system performs better than conventional retrieval engines.