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R. H. Goudar

Work place: Visvesvaraya Technological University, Belagavi

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Research Interests: Data Structures and Algorithms, Network Security, Network Architecture

Biography

Dr. R H Goudar, currently working as an Associate Professor, Dept. of Computer Network Engineering, Visvesvaraya Technological University, Belagavi. He has 13 years of Teaching Experience at Professional Institutes across India. He worked as a faculty Member at International Institute of Information Technology, Pune for 4 years and at Indian National Satellite Master Control Facility, Hassan, India. He published over 145 papers in International Journals, Book Chapters and Conferences of High Repute. He has guided over 140 M.Tech Dissertation and 04 ongoing Ph.D Students. Dr R H Goudar has received various awards like Outstanding Faculty Award, Research Performance Award, Young Faculty Award from VIFA, and Young Research Scientist Award from VGST Karnataka. He has received research grants from AICTE, UCOST and VGST, Karnataka. He has received over 754 citations for the work in subjects of Interest includes Semantic Web, Cloud, Big Data, Network Security and Wireless Sensor Networks.

Author Articles
Quine-McCluskey: A Novel Concept for Mining the Frequency Patterns from Web Data

By Bina Bhandari R. H. Goudar Kaushal Kumar

DOI: https://doi.org/10.5815/ijeme.2018.01.05, Pub. Date: 8 Jan. 2018

With the advancement in the web technology it is considered as one of the vast repository of information. However this information is in the hidden form.  Various data mining techniques need to be applied for extracting the meaningful information from the web. In this paper the various techniques are discussed that have been used by many researchers for extracting the information and also shown the disadvantages with the existing approaches. The paper put forward a novel concept of mining the association rule from the web data by using Quine-McCluskey algorithm. This algorithm is an optimization technique over the existing algorithm like Apriori, reverse Apriori, k-map. This paper exhibits the working of the Quine- McCluskey algorithm that can extract the frequently accessed web pages with minimum number of candidate sets generation. However the limitation of Quine-McCluskey algorithm is that it cannot find the infrequent patterns.

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