Poster Summary (2 pages)
Official ACM published version: http://doi.acm.org/10.1145/1571941.1572064
Author's copy: PDF (61KB)
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 δ 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 δ is in the range of [0.1, 0.9], AncestorRank can greatly improve BM25 performance, and in our experiments is often better than PageRank.
Poster summary in Proceedings of the 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 658-659, Boston, July 2009.
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