%0 Journal Article
	%A Atefeh Heydari and  Mohammadali Tavakoli and  Zuriati Ismail and  Naomie Salim
	%D 2016
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 109, 2016
	%T Leveraging Quality Metrics in Voting Model Based Thread Retrieval
	%U https://publications.waset.org/pdf/10003397
	%V 109
	%X Seeking and sharing knowledge on online forums
have made them popular in recent years. Although online forums are
valuable sources of information, due to variety of sources of
messages, retrieving reliable threads with high quality content is an
issue. Majority of the existing information retrieval systems ignore
the quality of retrieved documents, particularly, in the field of thread
retrieval. In this research, we present an approach that employs
various quality features in order to investigate the quality of retrieved
threads. Different aspects of content quality, including completeness,
comprehensiveness, and politeness, are assessed using these features,
which lead to finding not only textual, but also conceptual relevant
threads for a user query within a forum. To analyse the influence of
the features, we used an adopted version of voting model thread
search as a retrieval system. We equipped it with each feature solely
and also various combinations of features in turn during multiple
runs. The results show that incorporating the quality features
enhances the effectiveness of the utilised retrieval system
significantly.
	%P 122 - 128