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
Link To Document