%0 Journal Article
	%A Fereshteh Mahdavi and  Maizatul Akmar Ismail and  Noorhidawati Abdullah
	%D 2009
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 28, 2009
	%T Semi-Automatic Trend Detection in Scholarly Repository Using Semantic Approach
	%U https://publications.waset.org/pdf/4085
	%V 28
	%X Currently WWW is the first solution for scholars in
finding information. But, analyzing and interpreting this volume of
information will lead to researchers overload in pursuing their
research.
Trend detection in scientific publication retrieval systems helps
scholars to find relevant, new and popular special areas by
visualizing the trend of input topic.
However, there are few researches on trend detection in scientific
corpora while their proposed models do not appear to be suitable.
Previous works lack of an appropriate representation scheme for
research topics.
This paper describes a method that combines Semantic Web and
ontology to support advance search functions such as trend detection
in the context of scholarly Semantic Web system (SSWeb).
	%P 903 - 905