Article

Usage-Based PageRank for Web Personalization

Authors:

Magdalini Eirinaki,

Michalis VazirgiannisAuthors Info & Claims

ICDM '05: Proceedings of the Fifth IEEE International Conference on Data Mining

Pages 130 - 137

https://doi.org/10.1109/ICDM.2005.148

Published: 27 November 2005 Publication History

Abstract

Recommendation algorithms aim at proposing "next" pages to a user based on her current visit and the past users' navigational patterns. In the vast majority of related algorithms, only the usage data are used to produce recommendations, whereas the structural properties of the Web graph are ignored. We claim that taking also into account the web structure and using link analysis algorithms ameliorates the quality of recommendations. In this paper we present UPR, a novel personalization algorithm which combines usage data and link analysis techniques for ranking and recommending web pages to the end user. Using the web site's structure and its usage data we produce personalized navigational graph synopses (prNG) to be used for applying UPR and produce personalized recommendations. Experimental results show that the accuracy of the recommendations is superior to pure usage-based approaches.

References

[1]

M.S. Aktas, M.A. Nacar, F. Menczer, Personalizing PageRank Based on Domain Profiles, in Proc. of WEBKDD 2004 Workshop, August 2004, Seattle, USA.

[2]

R. Baraglia, F. Silvestri, An Online Recommender System for Large Web Sites, in Proc. of ACM/IEEE WI'04 Conference, China, September 2004.

Digital Library

[3]

J. Borges, M. Levene, Data Mining of User Navigation Patterns, in Revised Papers from the International Workshop on Web Usage Analysis and User Profiling, LNCS Vol. 1836, pp.92-111, 2000.

Digital Library

[4]

S. Brin, L. Page, The anatomy of a large-scale hypertextual Web search engine, Computer Networks, 30(1-7): 107-117, 1998, Proc. of WWW7 Conference.

Digital Library

[5]

A.G. Buchner, M. Baumgarten, S.S. Anand, M.D. Mulvenna, J.G. Hughes, Navigation pattern discovery from Internet data, in Proc. of WEBKDD'99 Workshop, August 1999, San Diego, CA.

Digital Library

[6]

I. Cadez, S. Gaffney, P. Smyth, A general probabilistic framework for clustering individuals and objects, in Proc. of ACM KDD2000 Conference, Boston, 2000.

Digital Library

[7]

I. Cadez, D. Heckerman, C. Meek, P. Smyth, S. White, Visualization of Navigation Patterns on a Web Site Using Model Based Clustering, in Proc. of ACM KDD2000 Conference, Boston MA, 2000.

Digital Library

[8]

M. Deshpande, G. Karypis, Selective Markov Models for Predicting Web-Page Accesses, in Proc. of the 1st SIAM International Conference on Data Mining, 2001.

[9]

M. Eirinaki, Web Mining: A Roadmap, Technical Report, DB-NET 2004, available at http://www.db-net.aueb.gr

[10]

M. Eirinaki, M. Vazirgiannis, Web Mining for Web Personalization, in ACM TOIT, 3(1), February 2003, pp.1-29.

Digital Library

[11]

M. Eirinaki, M. Vazirgiannis, I. Varlamis, SEWeP: Using Site Semantics and a Taxonomy to Enhance the Web Personalization Process, in Proc. of ACM KDD2003 Conference, August 2003, Washington DC.

Digital Library

[12]

M. El-Sayed, C. Ruiz, E.A. Rundensteiner, FS-Miner: Efficient and Incremental Mining of Frequent Sequence Patterns in Web Logs, in Proc. of WIDM '04, November 2004, Washington DC.

Digital Library

[13]

T. Haveliwala, Topic-Sensitive PageRank, in Proc. of WWW2002 Conference, Hawaii USA, May 2002.

Digital Library

[14]

M. Kendall, J.D. Gibbons, Rank Correlation Methods, Oxford University Press, 1990.

[15]

M. Levene, G. Loizou, Computing the Entropy of User Navigation in the Web, in Intl. Journal of Information Technology and Decision Making, 2:459-476, 2003.

[16]

E. Manavoglou, D. Pavlov, C.L. Giles, Probabilistic User Behaviour Models, in Proc. of ICDM 2003.

Digital Library

[17]

F. Masseglia, P. Poncelet, M. Teisseire, Using Data Mining Techniques on Web Access Logs to Dynamically Improve Hypertext Structure, in ACM Sig Web Letters, Vol. 8, N. 3, pp. 13-19, October 1999.

Digital Library

[18]

R. Motwani and P. Raghavan. Randomized Algorithms, Cambridge University Press, United Kingdom, 1995.

Digital Library

[19]

msnbc.com Web Log Data, available from UCI KDD Archive, http://kdd.ics.uci.edu/databases/msnbc/msnbc.html

[20]

M. Perkowitz, O. Etzioni, Towards Adaptive Web Sites: Conceptual Framework and Case Study, in Artificial Intelligence 118{1-2} (2000), pp. 245-275.

Digital Library

[21]

N. Polyzotis, M. Garofalakis, Structure and Value Synopses for XML Data Graphs, in Proc. of the 28th VLDB Conference, 2002.

Digital Library

[22]

N. Polyzotis, M. Garofalakis, Y. Ioannidis, Approximate XML Query Answers, in Proc. of SIGMOD 2004, Paris, France, June 2004.

Digital Library

[23]

M. Richardson, P. Domingos, The Intelligent Surfer: Probabilistic Combination of Link and Content Information in PageRank, in Neural Information Processing Systems, 14, pp.1441-1448, 2002.

[24]

R.R. Sarukkai, Link Prediction and Path Analysis Using Markov Chains, in Computer Networks, 33(1-6): 337-386, 2000.

Digital Library

[25]

R. Sen, M. Hansen, Predicting a Web user's next access based on log data, in Journal of Computational Graphics and Statistics, 12(1):143-155, 2003.

[26]

M. Spiliopoulou, L.C. Faulstich, and K. Wilkler, A data miner analyzing the navigational behaviour of Web users, in Proc. of the Workshop on Machine Learning in User Modelling, Greece, July 1999.

[27]

Q. Zhao, S.S. Bhowmick, Mining History of Changes to Web Access Patterns, in Proc. of PKDD 2004, Italy, September 2004.

Digital Library

Cited By

Gholami HChang C(2016)Situation-Aware Decision Making in Smart HomesProceedings of the 14th International Conference on Inclusive Smart Cities and Digital Health - Volume 967710.1007/978-3-319-39601-9_7(71-82)Online publication date: 25-May-2016
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Veningston KShanmugalakshmi RRangan PJayaraman B(2014)Information Retrieval by Document Re-ranking using Term Association GraphProceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing10.1145/2660859.2660927(1-8)Online publication date: 10-Oct-2014
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Zhukovskiy MKhropov AGusev GSerdyukov PJones GSheridan PKelly Dde Rijke MSakai T(2013)Fresh BrowseRankProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484186(1029-1032)Online publication date: 28-Jul-2013
https://dl.acm.org/doi/10.1145/2484028.2484186
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Index Terms

Usage-Based PageRank for Web Personalization

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Published In

cover image Guide Proceedings

ICDM '05: Proceedings of the Fifth IEEE International Conference on Data Mining

November 2005

837 pages

ISBN:0769522785

Publisher

IEEE Computer Society

United States

Publication History

Published: 27 November 2005

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Cited By

Gholami HChang C(2016)Situation-Aware Decision Making in Smart HomesProceedings of the 14th International Conference on Inclusive Smart Cities and Digital Health - Volume 967710.1007/978-3-319-39601-9_7(71-82)Online publication date: 25-May-2016
https://dl.acm.org/doi/10.1007/978-3-319-39601-9_7
Veningston KShanmugalakshmi RRangan PJayaraman B(2014)Information Retrieval by Document Re-ranking using Term Association GraphProceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing10.1145/2660859.2660927(1-8)Online publication date: 10-Oct-2014
https://dl.acm.org/doi/10.1145/2660859.2660927
Zhukovskiy MKhropov AGusev GSerdyukov PJones GSheridan PKelly Dde Rijke MSakai T(2013)Fresh BrowseRankProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484186(1029-1032)Online publication date: 28-Jul-2013
https://dl.acm.org/doi/10.1145/2484028.2484186
Fujiwara YNakatsuji MShiokawa HMishima TOnizuka MRoss KSrivastava DPapadias D(2013)Efficient ad-hoc search for personalized PageRankProceedings of the 2013 ACM SIGMOD International Conference on Management of Data10.1145/2463676.2463717(445-456)Online publication date: 22-Jun-2013
https://dl.acm.org/doi/10.1145/2463676.2463717
Anari ZMeybodi MAnari BSpyratos NKapetanios ETraina AChbeir RBadr Y(2009)Web page ranking based on fuzzy and learning automataProceedings of the International Conference on Management of Emergent Digital EcoSystems10.1145/1643823.1643853(162-166)Online publication date: 27-Oct-2009
https://dl.acm.org/doi/10.1145/1643823.1643853
Rosaci DSarné GGarruzzo S(2009)MUADDIBACM Transactions on Information Systems10.1145/1629096.162910227:4(1-41)Online publication date: 30-Nov-2009
https://dl.acm.org/doi/10.1145/1629096.1629102
Guo YRamamohanarao KPark L(2008)Web Page Prediction Based on Conditional Random FieldsProceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence10.5555/1567281.1567339(251-255)Online publication date: 27-Jun-2008
https://dl.acm.org/doi/10.5555/1567281.1567339
Su JWang BTseng V(2008)Effective Ranking and Recommendation on Web Page Retrieval by Integrating Association Mining and PageRankProceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 0310.1109/WIIAT.2008.49(455-458)Online publication date: 9-Dec-2008
https://dl.acm.org/doi/10.1109/WIIAT.2008.49
Eirinaki MVazirgiannis MKapogiannis DBonifati ALee D(2005)Web path recommendations based on page ranking and Markov modelsProceedings of the 7th annual ACM international workshop on Web information and data management10.1145/1097047.1097050(2-9)Online publication date: 4-Nov-2005
https://dl.acm.org/doi/10.1145/1097047.1097050

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