Web Contents Tracking by Learning of Page Grammars

D. Kukulenz, C. Reinke, N. Hoeller

Abstract

A significant fraction of Web data is available only for short periods of time. We consider methods to keep track and to record such dynamic information automatically. The main problems are to find adequate reload times for Web data in order to reduce network traffic, to improve the freshness of obtained data and to reduce the risk of loosing information. Previous approaches usually improve reload strategies for Web data by considering the change dynamics of pages, by modeling the behavior statistically and then by applying suitable reload strategies. Based on this approach we first give a precise definition of data changes on the Web. Page changes are described by a page decomposition which is based on the estimation of grammars. Based on this decomposition segments of Web pages are identified. The change behavior of individual segments is recorded and applied to optimize reload strategies. We show that the completeness of obtained data and the network traffic may be improved significantly by applying our new reload strategy.
Original languageEnglish
Title of host publication2008 Third International Conference on Internet and Web Applications and Services
Number of pages10
PublisherIEEE
Publication date01.06.2008
Pages416-425
ISBN (Print)978-0-7695-3163-2
DOIs
Publication statusPublished - 01.06.2008
Event3rd International Conference on Internet and Web Applications and Services - Athens, Greece
Duration: 08.06.200813.06.2008
Conference number: 73382

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