Skip to main content
SpringerLink
Log in
Book cover

Information Technology Convergence pp 375–385Cite as

Computing Personalized PageRank Based on Temporal-Biased Proximity

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 253))

Abstract

Dynamic behaviors of World Wide Web is one of the most important characteristics that challenge search engine administrators to manipulate their search collection. Web content and links are changed each day to provide up-to-date information. In addition, a fresh web page, like new news article, is often more interesting to web users than a stale one. Thus, an analysis of temporal activities of the Web can contribute to improve better search and result ranking. In this paper, we propose a web personalized link-based ranking scheme that incorporates temporal information extracted from historical page activities. We first quantify page modifications over time and design a time-proximity model used in calculating inverse propagation scores of web pages. These scores are then used as a bias of personalized PageRank for page authority assessment. We conduct the experiments on a real-world web collection gathered from the Internet Archive. The results show that our approach improves upon PageRank in ranking of search results with respect to human users’ preference.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   329.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    http://www.dmoz.org/

  2. 2.

    http://archive.org/

References

  1. Adamic LA, Huberman BA (2001) The web’s hidden order. Commun ACM 44(9):55–59

    Article  Google Scholar 

  2. Baeza-Yates RA, Ribeiro-Neto BA (1999) Modern Information Retrieval. ACM Press & Addison Wesley, New York

    Google Scholar 

  3. Berberich K, Vazirgiannis M, Weikum G (2006) Time-aware authority ranking. Internet Math 2(3):301–332

    Article  MathSciNet  Google Scholar 

  4. Brin S, Motwani R, Page L, Winograd T (1998) What can you do with a web in your pocket. IEEE Data Eng Bull 21(2):37–47

    Google Scholar 

  5. Brin S, Page L (1998) The anatomy of a large-scale hypertextual web search engine. Comput Netw ISDN 30(1–7):107–117

    Article  Google Scholar 

  6. Cho J, Roy S.(2004) Impact of search engines on page popularity. In: Proceeding of the 13th WWW Conf

    Google Scholar 

  7. Dai N, Davison BD (2010) Freshness matters: In flowers, food, and web authority. In: Proceeding of the 33th ACM SIGIR Conf

    Google Scholar 

  8. Gerani S, Carman M, Crestani F (2012) Aggregation methods for proximity-based opinion retrieval. ACM Trans. Inform. Syst., 30(4), article 26

    Google Scholar 

  9. Golub GH, Loan CFV (1996) Matrix Computations. Johns Hopkins University Press, Baltimore and London

    MATH  Google Scholar 

  10. Gyöngyi Z, Garcia-Molina H, Pederson J (2004) Combating web spam with TrustRank. In: Proceeding of the 30th Conf. on VLDB

    Google Scholar 

  11. Haveliwala TH (1999) Efficient computation of PageRank. Technical Report, Stanford InfoLab

    Google Scholar 

  12. Haveliwala TH (2003) Topic-sensitive pagerank: a context-sensitive ranking algorithm for web search. IEEE Trans Knowl Data Eng 15(4):784–796

    Article  Google Scholar 

  13. Järvelin K, Kekäläinen J (2000) IR evaluation methods for retrieving highly relevant documents. In: Proceeding of the 23rd ACM SIGIR Conf

    Google Scholar 

  14. Järvelin K, Kekäläinen J (2002) Cumulated gain-based evaluation of IR techniques. ACM Trans Inf Syst 20(4):422–446

    Article  Google Scholar 

  15. Jeh G, Widom J (2003) Scaling personalized web search. In: Proceeding of the 12th WWW Conference

    Google Scholar 

  16. Liu Y, Liu TY, Gao B, Ma Z, Li H (2010) A framework to compute page importance based on user behaviors. Inf Retrieval 13(1):22–45

    Article  Google Scholar 

  17. Lv Y, Zhai C (2009) Positional language models for information retrieval. In: Proceeding of the 32nd ACM SIGIR Conference

    Google Scholar 

  18. Page L, Brin S, Motwani R, Winograd T (1999) The PageRank citation ranking: Bringing order to the web. Technical Report, Stanford InfoLab

    Google Scholar 

  19. Petkova D, Croft WB (2007) Proximity-based document representation for named entity retrieval. In: Proceeding of the 16th ACM CIKM

    Google Scholar 

  20. Yu PS, Li X, Liu B (2005) Adding the temporal dimension to search—A case study in publication search. In: Proceeding of the International Conference on Web Intelligence

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Massive Information and Knowledge Engineering Laboratory, Department of Computer Engineering, Kasetsart University, Bangkok, 10900, Thailand

    Bundit Manaskasemsak, Pramote Teerasetmanakul & Arnon Rungsawang

  2. Engineering Laboratory in Theoretical Enumerable System,Department of Computer Engineering, Chulalongkorn University, Bangkok, 10330, Thailand

    Kankamol Tongtip & Athasit Surarerks

Authors
  1. Bundit Manaskasemsak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pramote Teerasetmanakul
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kankamol Tongtip
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Athasit Surarerks
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Arnon Rungsawang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bundit Manaskasemsak .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Dept. Information & Communication Engineering, Fukuoka Institute of Technology Fac. Information Engineering, Fukuoka, Japan

    Leonard Barolli

  3. Departament De Llenguatges I Sistemes Informàtics, Universitat Politècnica De Catalunya, Barcelona, Spain

    Fatos Xhafa

  4. Humanitas College, Kyung Hee University, Seoul, Korea, Republic of (South Korea)

    Hwa-Young Jeong

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media Dordrecht

About this paper

Cite this paper

Manaskasemsak, B., Teerasetmanakul, P., Tongtip, K., Surarerks, A., Rungsawang, A. (2013). Computing Personalized PageRank Based on Temporal-Biased Proximity. In: Park, J., Barolli, L., Xhafa, F., Jeong, HY. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_39

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-6996-0_39

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6995-3

  • Online ISBN: 978-94-007-6996-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation