document: Topical TrustRank : using topicality to combat web spam Web spam is behavior that attempts to deceive search engine ranking algorithms . TrustRank is a recent algorithm that can combat web spam . However , TrustRank is vulnerable in the sense that the seed set used by TrustRank may not be sufficiently representative to cover well the different topics on the Web . Also , for a given seed set , TrustRank has a bias towards larger communities . We propose the use of topical information to partition the seed set and calculate trust scores for each topic separately to address the above issues . A combination of these trust scores for a page is used to determine its ranking . Experimental results on two large datasets show that our Topical TrustRank has a better performance than TrustRank in demoting spam sites or pages . Compared to TrustRank , our best technique can decrease spam from the top ranked sites by as much as 43.1 % .
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