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Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
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STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
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SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
RANDOM '02 Proceedings of the 6th International Workshop on Randomization and Approximation Techniques
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FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Random Evolution in Massive Graphs
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
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ACM Transactions on Internet Technology (TOIT)
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IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Perturbation of the hyper-linked environment
COCOON'03 Proceedings of the 9th annual international conference on Computing and combinatorics
Approximating PageRank from In-Degree
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Cluster Based Personalized Search
WAW '09 Proceedings of the 6th International Workshop on Algorithms and Models for the Web-Graph
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Recently, there has been a surge of research activity in the area of Link Analysis Ranking, where hyperlink structures are used to determine the relative authority of Web pages. One of the seminal works in this area is that of Kleinberg [15], who proposed the Hits algorithm. In this paper, we undertake a theoretical analysis of the properties of the Hits algorithm on a broad class of random graphs. Working within the framework of Borodin et al.[7], we prove that on this class (a) the Hits algorithm is stable with high probability, and (b) the Hits algorithm is similar to the InDegree heuristic that assigns to each node weight proportional to the number of incoming links. We demonstrate that our results go through for the case that the expected in-degrees of the graph follow a power-law distribution, a situation observed in the actual Web graph [9]. We also study experimentally the similarity between Hits and InDegree, and we investigate the general conditions under which the two algorithms are similar.