期刊名称：International Journal of Computer, Information, and Systems Science, and Engineering
印刷版ISSN：1307-2331
出版年度：2008
卷号：02
期号：03
页码：179-179
出版社：World Academy of Science, Engineering and Technology
摘要：In the last few years, the Semantic Web gained scientific
acceptance as a means of relationships identification in knowledge
base, widely known by semantic association. Query about complex
relationships between entities is a strong requirement for many
applications in analytical domains. In bioinformatics for example, it is
critical to extract exchanges between proteins. Currently, the widely
known result of such queries is to provide paths between connected
entities from data graph. However, they do not always give good
results while facing the user need by the best association or a set
of limited best association, because they only consider all existing
paths but ignore the path evaluation. In this paper, we present an
approach for supporting association discovery queries. Our proposal
includes (i) a query language PmSPRQL which provides a multiparadigm
query expressions for association extraction and (ii) some
quantification measures making easy the process of association ranking.
The originality of our proposal is demonstrated by a performance
evaluation of our approach on real world datasets.
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