Web data extraction from scientific publishers’ website using heuristic algorithm

Web data extraction from scientific publishers’ website using heuristic algorithm

Автор: Umamageswari Kumaresan, Kalpana Ramanujam

Журнал: International Journal of Intelligent Systems and Applications @ijisa

Статья в выпуске: 10 vol.9, 2017 года.

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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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Structured data, Information Extraction, Deep web, wrapper, DOM Tree, template, JQuery, XPATH

Короткий адрес: https://sciup.org/15016424

IDR: 15016424   |   DOI: 10.5815/ijisa.2017.10.04

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