Incorporating Trust into Web Search

Incorporating Trust into Web Search (2007)

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by Lan Nie , Baoning Wu , Brian D. Davison

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Datum	Value	Source
TITLE	Incorporating Trust into Web Search ∗	SVM HeaderParse 0.2
AUTHOR NAME	Lan Nie	SVM HeaderParse 0.2
AUTHOR AFFIL	Department of Computer Science & Engineering; Lehigh University	SVM HeaderParse 0.2
AUTHOR NAME	Baoning Wu	SVM HeaderParse 0.2
AUTHOR AFFIL	Department of Computer Science & Engineering; Lehigh University	SVM HeaderParse 0.2
AUTHOR NAME	Brian D. Davison	SVM HeaderParse 0.2
AUTHOR AFFIL	Department of Computer Science & Engineering; Lehigh University	SVM HeaderParse 0.2
ABSTRACT	The Web today includes many pages intended to deceive search engines, in which content or links are created to attain an unwarranted result ranking. Since the links among web pages are used to calculate authority, ranking systems should take into consideration which pages contain content to be trusted and which do not. In this paper, we assume the existence of a mechanism, such as, but not limited to Gyöngyi et al.’s TrustRank, to estimate the trustworthiness of a given page. However, unlike existing work that uses trust to identify or demote spam pages, we propose how to incorporate a given trust estimate into the process of calculating authority for a cautious surfer. We apply a total of forty-five queries over two large, real-world datasets to demonstrate that incorporating trust into an authority calculation using our cautious surfer can improve PageRank’s precision at 10 by 11-26 % and average top-10 result quality by 53-81%. 1	SVM HeaderParse 0.2
YEAR	2007	SVM HeaderParse 0.2
CITATIONS	38 found	ParsCit 1.0