Using Baum-Welch Algorithm for Sharing Fine-Grained Knowledge in Mutual Environments

Author(s):

A.M.Pushpalatha , Christian College of Engg and Tech Dindigul,Tamilnadu-624619,India; Dr.A.Nirmal Kumar, Christian College of Engg and Tech Dindigul,Tamilnadu-624619,India

Keywords:

User Request, Traditional Expert Search, Preprocessing, LEGDP, d-iHMM, Advisor Search

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 Baum-Welch 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.

Other Details:

Manuscript Id	:	IJSTEV2I10028
Published in	:	Volume : 2, Issue : 10
Publication Date	:	01/05/2016
Page(s)	:	90-94

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