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Web spam which refers to any deliberate actions bringing to selected web pages an unjustifiable favorable relevance or importance is one of the major obstacles for high quality information retrieval on the web. Most of the existing web spam detection methods are supervised that require a large and representative training set of web pages. Moreover, they often assume some global information such as a large web graph and snapshots of a large collection of web pages. They developed efficient online link spam and term spam detection methods using spamicity. This paper presents a demonstration of OSD, an Online Spam Detection system which can efficiently calculate a spamicity score online for any page on the web.
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