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- W2994178845 abstract "Knowledge Sharing is an activity through which knowledge is exchanged among people, friends, families, communities or organizations. Mutual Environments, which enable company-wide global teams to identify the source of the antidote to a lack of preparedness. This paper investigates Fine grained knowledge sharing in collaborative environments.Two step framework is used. 1) Web surfing data are clustered into tasks by LEGDP (LaplacianEigenmap Gaussian DirichletProcess ) Model. 2) From Each Task Micro Aspects are extracted by d-iHMM (Discriminative-infinite Hidden Markov Model) model. And to find proper members for knowledge sharing, the expert search method is applied on the mined results. Existing Hidden Markov Models takes larger memory and execution time.Also it provides low accuracy results. To overcome this we propose BaumWelch algorithm.This algorithm is the extension of Hidden Markov Model. This provides more accuracy than HMM and also takes less execution time to find the best advisor for our related query." @default.
- W2994178845 created "2019-12-13" @default.
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- W2994178845 date "2016-05-01" @default.
- W2994178845 modified "2023-09-27" @default.
- W2994178845 title "Using Baum-Welch Algorithm for Sharing Fine- Grained Knowledge in Mutual Environments" @default.
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