A rule-based CBR approach for expert finding and problem diagnosis
Expert Systems with Applications: An International Journal
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Organization memory (OM) has been regarded as one of the most important resources in the enterprise. An OM captures stores and shares the valuable organization knowledge and thus esteem as a base of enterprise knowledge management. Due to the complexity of OM, structuring and accessing the huge amount of heterogeneous information will be a heavy workload. In this paper, for supporting learning and the sharing of knowledge of the informal documents, recommendations will be provided based on Case-Based Reasoning (CBR) techniques. And we propose an ontology-based approach model to retrieve formal, semi-formal or informal knowledge by specifying the meta-level description to improve the retrieval efficiency on the problems of daily task and furthermore to eliminate the possibility of information overload.