• DocumentCode
    3325909
  • Title

    MinG: An efficient algorithm to mine graphs for semantic associations

  • Author

    Hassan, Zyad ; Qadir, Muhammad Abdul

  • Author_Institution
    Dept. of Comput. Sci., Mohammad Ali Jinnah Univ., Islamabad, Pakistan
  • fYear
    2011
  • fDate
    11-13 July 2011
  • Firstpage
    59
  • Lastpage
    64
  • Abstract
    Data in semantic web is modelled in terms of directed labelled graph. Vertices of that graph represent entities and edges represent relationships between those entities. Semantic web allows the discovery of relations between entities using the ρ-operators. In this paper an algorithm to answer ρ-operators, that is, to find all paths between any two nodes from a graph is proposed. The algorithm is based on ρ-index, an indexing scheme presented in the PhD thesis of Barton. Our algorithm reduces the computational and space complexity of indexing by not creating a special type of adjacency matrix called Path Type Matrix at each level of indexing which Barton´s algorithm did. We only need Path Type Matrices at first and last level of indexing. Thus if an indexing has 100 levels, Barton requires Path Type Matrices at each level and we only require Path Type Matrices at level 1 and level 100.
  • Keywords
    computational complexity; data mining; directed graphs; indexing; matrix algebra; semantic Web; ρ-index; ρ-operators; MinG algorithm; adjacency matrix; computational complexity; directed labelled graph; graph edge; graph entity; graph mining; graph vertex; indexing; path type matrix; semantic Web; space complexity; Arrays; Complexity theory; Data mining; Data models; Indexing; Algorithm; Graph Traversal; Indexing; Mining; RDF; Semantic Web;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Networks and Information Technology (ICCNIT), 2011 International Conference on
  • Conference_Location
    Abbottabad
  • ISSN
    2223-6317
  • Print_ISBN
    978-1-61284-940-9
  • Type

    conf

  • DOI
    10.1109/ICCNIT.2011.6020908
  • Filename
    6020908