Umamageswari Kumaresan

Work place: New Prince Shri Bhavani College of Engineering & Technology, Chennai, 600073, India



Research Interests: Information Security, Data Mining, Information-Theoretic Security


Umamageswari Kumaresan is currently working as assistant professor in the Dept. of IT, at New Prince Shri Bhavani College of Engineering and Technology. She received her B.Tech in Computer Science and Engineering from Pondicherry Engineering College in 2005, her M.Tech in Computer Science and Engineering from Bharath University in 2010, and currently pursuing Ph.D. degree in Computer Science and Engineering in Pondicherrry Engineering College respectively. Her research interests include web mining, web data extraction, information security and sentiment analysis. She is a member of IAENG.

Author Articles
Web Data Extraction from Scientific Publishers’ Website Using Heuristic Algorithm

By Umamageswari Kumaresan Kalpana Ramanujam

DOI:, Pub. Date: 8 Oct. 2017

WWW is a huge repository of information and the amount of information available on the web is growing day by day in an exponential manner. End users make use of search engines like Google, Yahoo, and Bingo etc. for retrieving information. Search engines use web crawlers or spiders which crawl through a sequence of web pages in order to locate the relevant pages and provide a set of links ordered by relevancy. Those indexed web pages are part of surface web. Getting data from deep web requires form submission and is not performed by search engines. Data analytics and data mining applications depend on data from deep web pages and automatic extraction of data from deep web is cumbersome due to diverse structure of web pages. In the proposed work, a heuristic algorithm for automatic navigation and information extraction from journal’s home page has been devised. The algorithm is applied to many publishers website such as Nature, Elsevier, BMJ, Wiley etc. and the experimental results show that the heuristic technique provides promising results with respect to precision and recall values.

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