The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
A Survey on PageRank Computing
Open accessAbstract
This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much more complex challenge. Recently, significant effort has been invested in building sets of personalized PageRank vectors. PageRank is also used in many diverse applications other than ranking. We are interested in the theoretical foundations of the PageRank formulation, in the acceleration of PageRank computing, in the effects of particular aspects of web graph structure on the optimal organization of computations, and in PageRank stability. We also review alternative models that lead to authority indices similar to PageRank and the role of such indices in applications other than web search. We also discuss linkbased search personalization and outline some aspects of PageRank infrastructure from associated measures of convergence to link preprocessing.
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Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
The anatomy of a large-scale hypertextual Web search engine
Brin, S., & Page, L. (1998) · Computer Networks and ISDN Systems · doi:10.1016/s0169-7552(98)00110-x · Cited by 16,004
Information theory and statistical mechanics
Jaynes, E. T. (1957) · Physical Review · doi:10.1103/physrev.106.620 · Cited by 12,931
Haveliwala, T. H. (2002) · Proceedings of the 11th international conference on World Wide Web · doi:10.1145/511446.511513 · Cited by 1,567
(2003) · doi:10.5555/644108.644113 · Cited by 762
Bianchini, M., Gori, M., & Scarselli, F. (2005) · ACM Transactions on Internet Technology · doi:10.1145/1052934.1052938 · Cited by 539
Template detection via data mining and its applications
Bar-Yossef, Z., & Rajagopalan, S. (2002) · Proceedings of the 11th international conference on World Wide Web · doi:10.1145/511446.511522 · Cited by 271
Dill, S., Kumar, R., Mccurley, K. S., Rajagopalan, S., Sivakumar, D., & Tomkins, A. (2002) · ACM Transactions on Internet Technology · doi:10.1145/572326.572328 · Cited by 197
Using PageRank to Characterize Web Structure
Pandurangan, G., Raghavan, P., & Upfal, E. (2002) · Lecture Notes in Computer Science · doi:10.1007/3-540-45655-4_36 · Cited by 164
Algorithmic Challenges in Web Search Engines
Henzinger, M. R. (2004) · Internet Mathematics · doi:10.1080/15427951.2004.10129079 · Cited by 81
Cited by
Random walks and diffusion on networks
Masuda, N., Porter, M. A., & Lambiotte, R. (2017) · Physics Reports · doi:10.1016/j.physrep.2017.07.007 · Cited by 657
Adiabatic Quantum Algorithm for Search Engine Ranking
Garnerone, S., Zanardi, P., & Lidar, D. A. (2012) · Physical Review Letters · doi:10.1103/physrevlett.108.230506 · Cited by 102
In-Degree and PageRank: Why Do They Follow Similar Power Laws?
Litvak, N., Scheinhardt, W. R. W., & Volkovich, Y. (2007) · Internet Mathematics · doi:10.1080/15427951.2007.10129293 · Cited by 62
Distribution of PageRank Mass Among Principle Components of the Web
Avrachenkov, K., Litvak, N., & Pham, K. S. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-77004-6_2 · Cited by 29
Metadata
- Authors
- Berkhin, P.
- Venue
- Internet Mathematics
- Publisher
- Internet Mathematics
- Published
- 2005-01
- Volume
- 2
- Issue
- 1
- Pages
- 73-120
- ISSN
- 1542-7951 (ISSN-L)
- 1944-9488
- OpenAlex
- W2125493559
- Cited by
- 474
- References
- 11
- FWCI
- 44.49
- Type
- journal article
- Language
- en
- Open access
- bronze
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