Keyword-Based Similarity Using Automatically Generated Semantic Graph in an Online Community of Practice

摘要

Communities of Practice (CoPs) allow enhancing members learning and maintaining knowledge in a community memory as they evolve. Pertinent reuse of this knowledge could facilitate learning among the CoP members, increase their productivity and also improve the quality of their artefacts. In our online CoP environment, we include knowledge reuse based on the Case Based Reasoning (CBR) approach as one of the main functions, aiming at capitalizing the community knowledge. In fact, when a CoP member encounters a new problem, the first phase of the CBR cycle consists of retrieving previously experienced cases that are similar to the new problem. In this paper, we propose a keywords-based similarity using a semantic network that contains all potential keywords of the CoP's domain of interest, organized semantically. We also present our approach for automatically generating this semantic graph based on content extracted from an external source: the Wikipedia knowledge base.