Staff View: A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context

A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context

Researchers face difficulties in finding relevant papers to their research interest as the number of scientific publication is rapidly increasing on the web. Scientific paper recommenders have emerged as a leading solution to help researchers by automatically suggesting relevant and useful publicati...

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Main Authors:	Sakib, Nazmus, Ahmad, Rodina, Haruna, Khalid
Format:	Article
Published:	Institute of Electrical and Electronics Engineers 2020
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://eprints.um.edu.my/25190/ https://doi.org/10.1109/ACCESS.2020.2980589
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id	my.um.eprints.25190
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spelling	my.um.eprints.251902020-07-28T01:35:56Z http://eprints.um.edu.my/25190/ A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context Sakib, Nazmus Ahmad, Rodina Haruna, Khalid QA75 Electronic computers. Computer science Researchers face difficulties in finding relevant papers to their research interest as the number of scientific publication is rapidly increasing on the web. Scientific paper recommenders have emerged as a leading solution to help researchers by automatically suggesting relevant and useful publications. Several approaches have been proposed on improving recommender systems. However, most existing approaches depend on priori user profiles, and thus they cannot recommend papers to new user. Furthermore, the existing approaches utilize non-public contextual information, and thus it cannot adequately find similarities between papers due to copyright restrictions. Also, the existing approaches consider only single level paper-citation relation to identify similarities between papers. Considering the above challenges, this paper presents a collaborative filtering based recommendation approach for scientific papers that does not depend on priori user profiles and which utilizes only public contextual information. Using citation context, we utilized 2-level paper-citation relations to find hidden associations between papers. The rational underlying this approach is that, two papers are co-occurred with same cited paper(s) and two papers are co-occurring with same citing paper(s) are significantly similar to some extent. To evaluate the performance of the proposed approach, publicly available datasets are used to conduct extensive experiments. The experimental results demonstrate that the proposed approach has significantly outperforms the baseline approaches in terms of precision, recall, F1, mean average precision, and mean reciprocal rank, which are commonly used information retrieval metrics. The novelty of this study is that, with the proposed approach, researchers are able to find relevant and useful publications over the internet regardless of their previous research experiences and research area. © 2013 IEEE. Institute of Electrical and Electronics Engineers 2020 Article PeerReviewed Sakib, Nazmus and Ahmad, Rodina and Haruna, Khalid (2020) A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context. IEEE Access, 8. pp. 51246-51255. ISSN 2169-3536 https://doi.org/10.1109/ACCESS.2020.2980589 doi:10.1109/ACCESS.2020.2980589
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Sakib, Nazmus Ahmad, Rodina Haruna, Khalid A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context
description	Researchers face difficulties in finding relevant papers to their research interest as the number of scientific publication is rapidly increasing on the web. Scientific paper recommenders have emerged as a leading solution to help researchers by automatically suggesting relevant and useful publications. Several approaches have been proposed on improving recommender systems. However, most existing approaches depend on priori user profiles, and thus they cannot recommend papers to new user. Furthermore, the existing approaches utilize non-public contextual information, and thus it cannot adequately find similarities between papers due to copyright restrictions. Also, the existing approaches consider only single level paper-citation relation to identify similarities between papers. Considering the above challenges, this paper presents a collaborative filtering based recommendation approach for scientific papers that does not depend on priori user profiles and which utilizes only public contextual information. Using citation context, we utilized 2-level paper-citation relations to find hidden associations between papers. The rational underlying this approach is that, two papers are co-occurred with same cited paper(s) and two papers are co-occurring with same citing paper(s) are significantly similar to some extent. To evaluate the performance of the proposed approach, publicly available datasets are used to conduct extensive experiments. The experimental results demonstrate that the proposed approach has significantly outperforms the baseline approaches in terms of precision, recall, F1, mean average precision, and mean reciprocal rank, which are commonly used information retrieval metrics. The novelty of this study is that, with the proposed approach, researchers are able to find relevant and useful publications over the internet regardless of their previous research experiences and research area. © 2013 IEEE.
format	Article
author	Sakib, Nazmus Ahmad, Rodina Haruna, Khalid
author_facet	Sakib, Nazmus Ahmad, Rodina Haruna, Khalid
author_sort	Sakib, Nazmus
title	A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context
title_short	A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context
title_full	A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context
title_fullStr	A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context
title_full_unstemmed	A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context
title_sort	collaborative approach toward scientific paper recommendation using citation context
publisher	Institute of Electrical and Electronics Engineers
publishDate	2020
url	http://eprints.um.edu.my/25190/ https://doi.org/10.1109/ACCESS.2020.2980589
_version_	1680857007189393408
score	13.211869

A Collaborative Approach Toward Scientific Paper Recommendation Using Citation Context

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