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| Content Provider | ACM Digital Library |
|---|---|
| Author | Wang, Jian Davison, Brian D. |
| Abstract | 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. |
| Starting Page | 658 |
| Ending Page | 659 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781605584836 |
| DOI | 10.1145/1571941.1572064 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2009-07-19 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Link analysis Pagerank Probabilistic counting |
| Content Type | Text |
| Resource Type | Article |
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