Topic Modelling
Shanthala Nagaraja1, Kiran Yarehalli Chandrappa2
1Shanthala Nagaraja, Pursuing Ph.D, BNM Institute of Technology, College of Engineering, Bangalore (Karnataka), India.
2Dr. Kiran Y. C, Professor, BNM Institute of Technology, College of Engineering, Bangalore (Karnataka), India.
Manuscript received on 05 December 2019 | Revised Manuscript received on 13 December 2019 | Manuscript Published on 31 December 2019 | PP: 482-485 | Volume-9 Issue-2S December 2019 | Retrieval Number: B11241292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1124.1292S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the history of information and technology the knowledge which was generated is stored in the form of digital technology. In present day the search engines will search based on terms and extract the list of similar documents from many topics. In this paper, the proposed Topic Modelling techniques will search based on the group of words from each document. The aim behind proposed topic modelling techniques is to comprise the topics from each of the document. The hidden topics from the list of collected text documents can be extracted using proposed probabilistic topic modelling.
Keywords: Modelling Information Digital.
Scope of the Article: Software Domain Modelling and Analysis