Matrix computations (3rd ed.)
The art of computer programming, volume 3: (2nd ed.) sorting and searching
The art of computer programming, volume 3: (2nd ed.) sorting and searching
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Respect my authority!: HITS without hyperlinks, utilizing cluster-based language models
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Hits on the web: how does it compare?
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Hits hits TREC: exploring IR evaluation results with network analysis
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Hits on question answer portals: exploration of link analysis for author ranking
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Comparing the effectiveness of hits and salsa
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Survey of Text Mining II: Clustering, Classification, and Retrieval
Survey of Text Mining II: Clustering, Classification, and Retrieval
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How many iterations does the (ever more) popular HITS algorithm require to converge in score and, perhaps more importantly, in rank (i.e. to get the nodes of a graph "in the right order")? After pinning down the elusive notion of convergence in rank we provide the first non-trivial bounds on the convergence of HITS. A "worst case" example, requiring a number of iterations superexponential in the size of the target graph to achieve even "mild" convergence, suggests the need for greater caution in the experimental evaluation of the algorithm - as recent results of poor performance (e.g. vs. SALSA) might be due to insufficient iterations, rather than to an intrinsic deficiency of HITS. An almost matching upper bound shows that, as long as one employs exponential acceleration e.g. through a "squaring trick", a polynomial running time (practical in many application domains) always provides strong convergence guarantees.