Efficient Algorithms for Finding Approximate Heavy Hitters in Personalized PageRanks-Reference-Cited by-同舟云学术

Efficient Algorithms for Finding Approximate Heavy Hitters in Personalized PageRanks

Published:2018-05-27 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 International Conference on Management of Data
language:
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Author:

Wang Sibo¹,Tao Yufei²

Affiliation:

1. University of Queensland, Brisbane, Australia

2. Chinese University of Hong Kong, Hong Kong, Hong Kong

Funder

Chinese University of Hong Kong

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3183713.3196919

Reference31 articles.

1. Reid Andersen Christian Borgs Jennifer T. Chayes John E. Hopcroft Vahab S. Mirrokni and Shang-Hua Teng. 2007. Local Computation of PageRank Contributions. In WAW. 150--165. Reid Andersen Christian Borgs Jennifer T. Chayes John E. Hopcroft Vahab S. Mirrokni and Shang-Hua Teng. 2007. Local Computation of PageRank Contributions. In WAW. 150--165.

2. Local Graph Partitioning using PageRank Vectors

3. Monte Carlo Methods in PageRank Computation: When One Iteration is Sufficient

4. Lars Backstrom and Jure Leskovec. 2011. Supervised random walks: predicting and recommending links in social networks. In WSDM. 635--644. 10.1145/1935826.1935914 Lars Backstrom and Jure Leskovec. 2011. Supervised random walks: predicting and recommending links in social networks. In WSDM. 635--644. 10.1145/1935826.1935914

5. Bahman Bahmani Kaushik Chakrabarti and Dong Xin. 2011. Fast personalized PageRank on MapReduce. In SIGMOD. 973--984. 10.1145/1989323.1989425 Bahman Bahmani Kaushik Chakrabarti and Dong Xin. 2011. Fast personalized PageRank on MapReduce. In SIGMOD. 973--984. 10.1145/1989323.1989425

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