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Hierarchical Web Structuring from the Web as a Graph Approach with Repetitive Cycle Proof

  • Wookey Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3842)

Abstract

The WWW can be viewed as digraph with Web nodes and arcs, where the Web nodes correspond to HTML files having page contents and the arcs correspond to hypertext links interconnected with the Web pages. The Web cycle resolution is one of the problems to derive a meaningful structure out of the complex WWW graphs. We formalize our view of the Web structure from Web as a graph approach to an algorithm in terms of proofing the repetitive cycles. We formalize the Web model that prevents the Web structuring algorithm from being bewildered by the repetitive cycles. The complexity of the corresponding algorithm has been addressed fairly enhanced than the previous approaches.

Keywords

Link Weight Semantic Distance Graph Approach Uniform Resource Identifier Information Processing Letter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Barabasi, A., Albert, R., Jeong, H.: Scale-free Characteristics of Random Networks: the Topology of the World-Wide Web. Physica A 281, 69–77 (2000)CrossRefGoogle Scholar
  2. 2.
    Garofalakis, M., Kappos, P., Mourloukos, D.: Web Site Optimization Using Page Popularity. IEEE Internet Computing 3(4), 22–29 (1999)CrossRefGoogle Scholar
  3. 3.
    Glover, E.J., Tsioutsiouliklis, C., Lawrence, S., Pennock, D., Flake, G.: Using Web Structure for Classifying and Describing Web Pages. In: Proc. WWW, pp. 562–569 (2002)Google Scholar
  4. 4.
    Gurrin, C., Smeaton, A.F.: Replicating Web Structure in Small-Scale Test Collections. Information Retrieval 7(3), 239–263 (2004)CrossRefGoogle Scholar
  5. 5.
    Henzinger, M.R., Heydon, A., Mitzenmacher, M., Najork, M.: On near-uniform URL sampling. Computer Networks 33(1), 295–308 (2000)CrossRefGoogle Scholar
  6. 6.
    Kumar, R., Raghavan, P., Rajagopalan, S., Tomkins, A.: Crawling the Web for cyber communities in the Web. In: Proc. 8th WWW, pp. 403–415 (1999)Google Scholar
  7. 7.
    Lee, W., Kim, S., Kang, S.: Dynamic Hierarchical Website Structuring Using Linear Programming. In: Bichler, M., Pröll, B. (eds.) EC-Web 2004. LNCS, vol. 3182, pp. 328–337. Springer, Heidelberg (2004)Google Scholar
  8. 8.
    Lee, W., Geller, J.: Semantic Hierarchical Abstraction of Web Site Structures for Web Searchers. Journal of Research and Practice in Information Technology 36(1), 71–82 (2004)Google Scholar
  9. 9.
    Mendelzon, A.O., Milo, T.: Formal Model of Web Queries. In: ACM PODS, pp. 134–143 (1997)Google Scholar
  10. 10.
    Nivasch, G.: Cycle detection using a stack. Information Processing Letters 90(3), 135–140 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
  11. 11.
    Pandurangan, G., Raghavan, P., Upfal, E.: Using PageRank to Characterize Web Structure. In: Ibarra, O.H., Zhang, L. (eds.) COCOON 2002. LNCS, vol. 2387, pp. 330–339. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  12. 12.
    Shmueli, O.: Dynamic Cycle Detection. Information Processing Letters 17(4), 185–188 (1983)zbMATHCrossRefMathSciNetGoogle Scholar
  13. 13.
    Thom, L.H., Iochpe, C.: Integrating a Pattern Catalogue in a Business Process Model. In: Proc. ICEIS, vol. 3, pp. 651–654 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Wookey Lee
    • 1
  1. 1.Computer ScienceSungkyul UniversityAnyangKorea

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