research-article

Integrating context-awareness and multi-criteria decision making in educational learning

Authors:

Shephalika Shekhar,

Alisha Anna Jose,

Sunil Kumar RaiAuthors Info & Claims

SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

Pages 2453 - 2460

https://doi.org/10.1145/3297280.3297522

Published: 08 April 2019 Publication History

Abstract

Recommender system is a well-known information system which can capture user tastes and produce item recommendations to the end users. Context-aware recommender systems (CARS) additionally take contexts (e.g., location, time, weather, etc) into consideration, and multi-criteria recommender systems (MCRS) utilize user preferences in multiple criteria to better generate recommendations. Both CARS and MCRS have been widely applied in the real-world applications, such as tourism, movies, music and dining. However, there are no existing research which exploits the methods to integrate them together, not to mention the contributions in the area of educational learning. In this paper, we make the first attempt to integrate context-awareness and multi-criteria decision making in the recommender systems by using the educational data as a case study. Our experimental results reveal that it is able to help produce more accurate recommendations by taking advantage of these two recommendation strategies. We also perform experiments on a tourism data set to demonstrate that the proposed methods can also be generalized to other domains.

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Cited By

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Raaj KMurmu MKanalli SKorgaokar TVanahalli MPrasad PSinha B(2024)Integrating Context and Criteria in Hotel Recommendations: A Deep Learning Perspective2024 International Conference on Computing, Sciences and Communications (ICCSC)10.1109/ICCSC62048.2024.10830411(1-5)Online publication date: 24-Oct-2024
https://doi.org/10.1109/ICCSC62048.2024.10830411
Afzal IYilmazel BKaleli C(2024)An Approach for Multi-Context-Aware Multi-Criteria Recommender Systems Based on Deep LearningIEEE Access10.1109/ACCESS.2024.342863012(99936-99948)Online publication date: 2024
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Index Terms

Integrating context-awareness and multi-criteria decision making in educational learning
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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cover image ACM Conferences

SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing

April 2019

2682 pages

ISBN:9781450359337

DOI:10.1145/3297280

Conference Chairs:
Chih-Cheng Hung
Kennesaw State University, Marietta, Georgia
,
George A. Papadopoulos
University of Cyprus, Nicosia, Cyprus

Copyright © 2019 ACM.

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Published: 08 April 2019

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SAC '19: The 34th ACM/SIGAPP Symposium on Applied Computing

April 8 - 12, 2019

Limassol, Cyprus

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Bickley SMacintyre ATorgler B(2024)Artificial Intelligence and Big Data in Sustainable EntrepreneurshipJournal of Economic Surveys10.1111/joes.1261139:1(103-145)Online publication date: 11-Jan-2024
https://doi.org/10.1111/joes.12611
Raaj KMurmu MKanalli SKorgaokar TVanahalli MPrasad PSinha B(2024)Integrating Context and Criteria in Hotel Recommendations: A Deep Learning Perspective2024 International Conference on Computing, Sciences and Communications (ICCSC)10.1109/ICCSC62048.2024.10830411(1-5)Online publication date: 24-Oct-2024
https://doi.org/10.1109/ICCSC62048.2024.10830411
Afzal IYilmazel BKaleli C(2024)An Approach for Multi-Context-Aware Multi-Criteria Recommender Systems Based on Deep LearningIEEE Access10.1109/ACCESS.2024.342863012(99936-99948)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3428630
Shrivastava RSisodia DNagwani N(2024)Deep ensembled multi-criteria recommendation system for enhancing and personalizing the user experience on e-commerce platformsKnowledge and Information Systems10.1007/s10115-024-02187-366:12(7799-7836)Online publication date: 4-Sep-2024
https://dl.acm.org/doi/10.1007/s10115-024-02187-3
Reguragui SBendahmane ALahiala A(2024)A Comprehensive Review of Context-Aware Recommender Systems in EducationRadical Solutions for Artificial Intelligence and Digital Transformation in Education10.1007/978-981-97-8638-1_10(143-163)Online publication date: 18-Dec-2024
https://doi.org/10.1007/978-981-97-8638-1_10
Abu-Rasheed HWeber CFathi M(2023)Context based learning: a survey of contextual indicators for personalized and adaptive learning recommendations – a pedagogical and technical perspectiveFrontiers in Education10.3389/feduc.2023.12109688Online publication date: 27-Jul-2023
https://doi.org/10.3389/feduc.2023.1210968
Shrivastava RSingh Sisodia DKumar Nagwani N(2023)Deep neural network-based multi-stakeholder recommendation system exploiting multi-criteria ratings for preference learningExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.119071213:PBOnline publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.eswa.2022.119071
Jiang PXin KLi C(2022)Deep Transfer Tensor Factorization for Multi-View Learning2022 IEEE International Conference on Data Mining Workshops (ICDMW)10.1109/ICDMW58026.2022.00067(459-466)Online publication date: Nov-2022
https://doi.org/10.1109/ICDMW58026.2022.00067
Zheng YWang D(2022)Multi-Criteria Ranking: Next Generation of Multi-Criteria Recommendation FrameworkIEEE Access10.1109/ACCESS.2022.320182110(90715-90725)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3201821
Dridi RTamine LSlimani Y(2022)Exploiting context-awareness and multi-criteria decision making to improve items recommendation using a tripartite graph-based modelInformation Processing and Management: an International Journal10.1016/j.ipm.2021.10286159:2Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.ipm.2021.102861
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