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A novel representation of graph structures in web mining and data analysis

Author

Listed:
  • Blazewicz, Jacek
  • Pesch, Erwin
  • Sterna, Malgorzata

Abstract

The paper presents a new graph representation, the graph matrix, which combines the adjacency matrix with the linked lists allowing for the fastest possible access to different types of information on a graph. This is increasingly important for a high search performance, for instance, for rapidly extracting information from the link structure in a hub and authority graph of the World-Wide-Web. A very recent application for the proposed data structure arises from categorical data clustering defining proximity and similarity of data through their patterns of co-occurrence.

Suggested Citation

  • Blazewicz, Jacek & Pesch, Erwin & Sterna, Malgorzata, 2005. "A novel representation of graph structures in web mining and data analysis," Omega, Elsevier, vol. 33(1), pages 65-71, February.
    • Handle: RePEc:eee:jomega:v:33:y:2005:i:1:p:65-71
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    References listed on IDEAS

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    1. Ulrich Dorndorf & Erwin Pesch, 1994. "Fast Clustering Algorithms," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 141-153, May.
    2. Blazewicz, Jacek & Pesch, Erwin & Sterna, Malgorzata, 2000. "The disjunctive graph machine representation of the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 127(2), pages 317-331, December.
    3. Steve Lawrence & C. Lee Giles, 1999. "Accessibility of information on the web," Nature, Nature, vol. 400(6740), pages 107-107, July.
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    Cited by:

    1. Ballings, Michel & Van den Poel, Dirk & Bogaert, Matthias, 2016. "Social media optimization: Identifying an optimal strategy for increasing network size on Facebook," Omega, Elsevier, vol. 59(PA), pages 15-25.

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