Accelerating the process of web page segmentation via template clustering. (2016)

• Record Type: Journal Article
• Authors: Zeleny, Jan; Burget, Radek
• Is Part Of: International journal of intelligent information and database systems. Volume 9:Number 2(2016)
• Page Start: 134
• Page End: 154
• Publication Date: 2016
• Subjects: VIPS -- page segmentation -- vision-based page segmentation -- web page segmentation -- web page preprocessing -- segmentation performance -- template detection -- template clustering -- data mining -- visual perception -- web templates; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

Page segmentation is often one of the initial steps when performing data mining on a web page. In the past years, several methods of page segmentation have been developed that are based on visual perception of the web page. In this paper, we propose a generic method for improving efficiency of virtually all vision-based segmentation algorithms. Our method called cluster-based page segmentation takes the widely spread concept of web templates and utilises it for improving the efficiency of vision-based page segmentation by clustering web pages and performing the segmentation on the clusters instead of each page in the cluster. To prove the efficiency of our algorithm, we offer experimental results gathered using three different vision-based segmentation algorithms.