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Survey Paper | Computer Science & Engineering | India | Volume 3 Issue 12, December 2014 | Rating: 6.2 / 10
A Survey Report on: Methodology for Extraction of Information from Web Pages by Using Clustering Algorithm
Mahesh Dabade, Shriniwas Gadage
Abstract: This paper is about data extraction from top-k web pages, which explain top k occurrences of a subject that will be of ordinary interest. For example Best Catches ever, 50 best Android diversions 2014: our top picks, and so on. Contrasted with other sorted out data on the web including advertizing data, data in top-k gives is bigger and effective, of high caliber, and by and large additional fascinating. In this way best k gives are very important. For sample, it will likewise help improve open-domain information bottoms (to help projects, for example, inquiry or reality replying). In this report, we introduce an efficient system that extracts top-k providers from pages with superior performance. Specifically, we procure more than 1.69 million top-k gives from a site corpus of 1.59 billion pages with 91.9 % exactness and 72.29 % review.
Keywords: data extraction, top-k provides, record extraction, open-domain information, clustering
Edition: Volume 3 Issue 12, December 2014,
Pages: 345 - 347