Probabilistic counting algorithms for data base applications
Journal of Computer and System Sciences
The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
ANF: a fast and scalable tool for data mining in massive graphs
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Link analysis for Web spam detection
ACM Transactions on the Web (TWEB)
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The AncestorRank algorithm calculates an authority score by using just one characteristic of the web graph-the number of ancestors per node. For scalability, we estimate the number of ancestors by using a probabilistic counting algorithm. We also consider the case in which ancestors which are closer to the node have more influence than those farther from the node. Thus we further apply a decay factor delta on the contributions from successively earlier ancestors. The resulting authority score is used in combination with a content-based ranking algorithm. Our experiments show that as long as delta is in the range of [0.1, 0.9], AncestorRank can greatly improve BM25 performance, and in our experiments is often better than PageRank.