research-article

A systematic review of scholar context-aware recommender systems

Authors:

Zohreh Dehghani Champiri,

Seyed Reza Shahamiri,

Siti Salwah Binti SalimAuthors Info & Claims

Expert Systems with Applications: An International Journal, Volume 42, Issue 3

Pages 1743 - 1758

https://doi.org/10.1016/j.eswa.2014.09.017

Published: 15 February 2015 Publication History

Abstract

We review the relevant articles in the field of scholar recommendations.We explore contextual information influential in scholar recommendations.We examine recommending approaches.Contextual information are categorised in three groups.The most recommending approaches are collaborative filtering, content based, knowledge based and hybrid. Incorporating contextual information in recommender systems is an effective approach to create more accurate and relevant recommendations. This review has been conducted to identify the contextual information and methods used for making recommendations in digital libraries as well as the way researchers understood and used relevant contextual information from the years 2001 to 2013 based on the Kitchenham systematic review methodology. The results indicated that contextual information incorporated into recommendations can be categorised into three contexts, namely users' context, document's context, and environment context. In addition, the classical approaches such as collaborative filtering were employed more than the other approaches. Researchers have understood and exploited relevant contextual information through four ways, including citation of past studies, citation of past definitions, self-definitions, and field-query researches; however, citation of the past studies has been the most popular method. This review highlights the need for more investigations on the concept of context from user viewpoint in scholarly domains. It also discusses the way a context-aware recommender system can be effectively designed and implemented in digital libraries. Additionally, a few recommendations for future investigations on scholarly recommender systems are proposed.

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cover image Expert Systems with Applications: An International Journal

Expert Systems with Applications: An International Journal Volume 42, Issue 3

February 2015

817 pages

ISSN:0957-4174

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Copyright © Elsevier Ltd.

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Pergamon Press, Inc.

United States

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Published: 15 February 2015

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Zitouni HMeshoul SMezioud C(2022)New contextual collaborative filtering system with application to personalized healthy nutrition educationJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2020.04.01234:4(1124-1137)Online publication date: 1-Apr-2022
https://dl.acm.org/doi/10.1016/j.jksuci.2020.04.012
Rabiu ISalim NDa'u ANasser M(2022)Modeling sentimental bias and temporal dynamics for adaptive deep recommendation systemExpert Systems with Applications: An International Journal10.1016/j.eswa.2021.116262191:COnline publication date: 6-May-2022
https://dl.acm.org/doi/10.1016/j.eswa.2021.116262
Wang ZChen CZheng PLi XSong W(2022)A hypergraph-based approach for context-aware smart product-service system configurationComputers and Industrial Engineering10.1016/j.cie.2021.107816163:COnline publication date: 1-Jan-2022
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Bunnell LOsei-Bryson KYoon V(2020)RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems ResearchersInformation Systems Frontiers10.1007/s10796-019-09935-922:6(1377-1418)Online publication date: 1-Dec-2020
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Champiri ZFisher BFreund L(2020)rScholar: An Interactive Contextual User Interface to Enhance UX of Scholarly Recommender SystemsHCI International 2020 - Late Breaking Papers: User Experience Design and Case Studies10.1007/978-3-030-60114-0_43(662-686)Online publication date: 19-Jul-2020
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