Abstract: In this paper, we present FoCUS (Forum Crawler under Supervision), a supervised web-scale forum crawler. The aim of FoCUS is to only probe relevant forum content from the web with minimal overhead. Forum threads contain information content that is the target of forum crawlers. Although forums have different layouts or styles and are powered by different forum software packages, they always have similar implicit navigation paths connected by specific URL types to lead users from entry pages to thread pages. Based on this observation, we reduce the web forum crawling problem to a URL type recognition troubles and show how to learn accurate and effective regular expression patterns of implicit steering paths from an automatically created training set using aggregated results from weak page type classifiers. Robust page type classifiers can be trained from as few as 5 annotated forums and applied to a large set of unseen forums. Our test results show that FoCUS achieved over 98% effectiveness and 97% coverage on a large set of test forums powered by over 150 different forum software packages.
Keywords: Navigation Paths, Thread Pages, Robust page.
Title: FoCUS: Forum Crawler under Supervision
Author: G.Hema Kumar, G.K.Venkata Narasimha Reddy
International Journal of Computer Science and Information Technology Research
ISSN 2348-120X (online), ISSN 2348-1196 (print)
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