Fine Grained Knowledge Sharing Mechanism with Hierarchical Structure Using Iterative d-iHMM

Authors

  • Saraswati Sonkale Department of Computer Engineering, D.Y.Patil COE, Akurdi,Savitribai Phule Pune University, Pune
  • Mrs. V.L.Kolhe Department of Computer Engineering, D.Y.Patil COE, Akurdi,Savitribai Phule Pune University, Pune

Keywords:

Advisor search, text mining, Dirichlet processes, graphical models, Hierarchical Clustering, d-iHMM

Abstract

In collaborative environments, individuals may attempt to acquire similar information on the web keeping in
mind the end goal to pick up data in one domain. For instance, in an organization a few divisions might progressively
need to purchase business insight software and representatives from these offices may have to learn online about
different business intelligence tools & their characteristics independently. A two-stage framework is used for mining finegrained data:(1) Web surfing information is grouped into clusters by using hierarchical clustering; (2) a novel
discriminative infinite Hidden Markov Model is used iteratively to mine fine-grained data from every task. The excellent
master inquiry technique is connected to mined results to discover appropriate individuals for information sharing.

Downloads

Published

2017-07-25

How to Cite

Saraswati Sonkale, & Mrs. V.L.Kolhe. (2017). Fine Grained Knowledge Sharing Mechanism with Hierarchical Structure Using Iterative d-iHMM. International Journal of Advance Engineering and Research Development (IJAERD), 4(7), 366–371. Retrieved from https://www.ijaerd.org/index.php/IJAERD/article/view/3196

Issue

Vol. 4 No. 7 (2017): Volume 4 Issue 7 JULY 2017

Section

Articles