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On Measuring the Contextual Relevance of Research Paper Recommendation Systems


Haruna, Khalid and Ismail, Maizatul Akmar (2018) On Measuring the Contextual Relevance of Research Paper Recommendation Systems. In: Knowledge Management International Conference (KMICe) 2018, 25 –27 July 2018, Miri Sarawak, Malaysia.

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Abstract

The contextual information present in scholarly papers plays a vital role in the implementation of research paper recommendation systems. However, the most critical concern is how to measure the contextual relevance of scholarly papers for better recommendations? In this paper, we present the most common approaches used to measure the contextual relevance of research paper recommendation systems. Based on the research outcome, content-link, citation relation, social network analyses, and their combinations are the most widely used. The paper also outlined the strengths and weaknesses of each approach.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN: 9789670910871 Organized by: School of Computing, College of Arts and Sciences, Universiti Utara Malaysia.
Uncontrolled Keywords: Content-link analysis, citation relation analysis, social network analysis, contextual relevance, recommendation systems.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: School of Computing
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 25 Nov 2018 02:38
Last Modified: 25 Nov 2018 02:38
URI: http://repo.uum.edu.my/id/eprint/25223

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