Hou Honglun
Department of Computer Science and Engineering, Zhejiang University City College, Hangzhou, 310015, China
Wu Minghui
Department of Computer Science and Engineering, Zhejiang University City College, Hangzhou, 310015, China
ABSTRACT
As personalized PageRank has been widely leveraged for ranking on graph-structured scenarios; its computation efficiency becomes a prominent issue. In this study, the authors survey on an array of work that concentrate on efficient and scalable Personalized PageRank (PPV) computation, ranging from earlier work that attempt to use partial precomputation to improve online efficiency, to recent work that estimate approximate PPV for full personalization and the hybrid methods. A comparison about these methods in terms of the ability of personalization, scalability, online/offline efficiency and accuracy and a few possible research directions are presented at the end of this study.
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Received: August 05, 2013;
Accepted: November 04, 2013;
Published: November 12, 2013
How to cite this article
Hou Honglun and Wu Minghui, 2013. Efficient Personalized Pagerank Computation: A Survey. Journal of Applied Sciences, 13: 4892-4896.
DOI: 10.3923/jas.2013.4892.4896
URL: https://scialert.net/abstract/?doi=jas.2013.4892.4896
DOI: 10.3923/jas.2013.4892.4896
URL: https://scialert.net/abstract/?doi=jas.2013.4892.4896
REFERENCES
- Bahmani, B., A. Chowdhury and A. Goel, 2010. Fast incremental and personalized PageRank. Proc. VLDB Endowment, 4: 173-184.
Direct Link - Berkhin, P., 2006. Bookmark-coloring algorithm for personalized pagerank computing. Internet Math., 3: 41-62.
CrossRef - Chakrabarti, S., 2007. Dynamic personalized pagerank in entity-relation graphs. Proceedings of the 16th International Conference on World Wide Web, May 8-12, 2007, Banff, Canada, pp: 571-580.
CrossRef - Fogaras, D., B. Racz, K. Csalogany and T. Sarlos, 2005. Towards scaling fully personalized pagerank: Algorithms, lower bounds and experiments. Internet Math., 2: 333-358.
CrossRef - Haveliwala, T.H., 2003. Topic-sensitive PageRank: A context-sensitive ranking algorithm for web search. IEEE Trans. Knowledge Data Eng., 15: 784-796.
CrossRef - Ilyas, I.F., G. Beskales and M.A. Soliman, 2008. A survey of top-k query processing techniques in relational database systems. ACM Comput. Surv., Vol. 40, No. 4.
CrossRef - Jeh, G. and J. Widom, 2003. Scaling personalized web search. Proceedings of the 12th International Conference on World Wide Web, May 20-24, 2003, Budapest, Hungary, pp: 271-279.
CrossRef - Kamvar, S.D., T.H. Haveliwala, C.D. Manning and G.H. Golub, 2003. Extrapolation methods for accelerating PageRank computations. Proceedings of the 12th International Conference on World Wide Web, May 20-24, 2003, Budapest, Hungary, pp: 261-270.
CrossRef - Nie, Z., Y. Zhang, J. Wen and W. Ma, 2005. Object-level ranking: Bringing order to web objects. Proceedings of the 14th International Conference on World Wide Web, May 10-14, 2005, Chiba, Japan, pp: 567-574.
CrossRef - Richardson, M. and P. Domingos, 2002. The Intelligent Surfer: Probabilistic Combination of Link and Content Information in PageRank. In: Advances in Neural Information Processing Systems 14, Dietterich, T.G., S. Becker and Z. Ghahramani (Eds.). Vol. 1, MIT Press, USA., ISBN-13: 9780262042062, pp: 1441-1448.