A Literature Review of Recommender Systems for the Cultural Sector

Nguyen Dam, Thang Dinh

Abstract

Nowadays, organizations in the cultural sector have faced the problem of improving the discoverability of their products to meet the target objective regardless of the tremendous amount of information. In this respect, recommender systems have been proven to be the solution for enterprises, especially for cultural small and medium-sized organizations and enterprises (SMOs/SMEs), to enhance the discoverability of their products. This study aims at presenting a concept-centric literature review of recommender systems for cultural SMEs/SMOs to identify the current status-quo of the application in six cultural domains, including heritage and libraries, live performance, visual and applied arts, written and published works, audio-visual and interactive media, and sound recording. The finding of this paper reveals the adoption of recommender systems of cultural SMOs/SMEs is still in the early stage of maturity. The specific status-quo of recommender system adoption in each cultural domain is uncovered through the literature review. Other relevant aspects, which relate to data sources, data mining models, and algorithms, are also discussed in detail. Finally, the paper proposes future research directions to promote the application of artificial intelligence in general, and recommender systems, in particular, in the cultural sector.

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Paper Citation


in Harvard Style

Dam N. and Dinh T. (2020). A Literature Review of Recommender Systems for the Cultural Sector.In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-423-7, pages 715-726. DOI: 10.5220/0009337807150726


in Bibtex Style

@conference{iceis20,
author={Nguyen Dam and Thang Dinh},
title={A Literature Review of Recommender Systems for the Cultural Sector},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2020},
pages={715-726},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009337807150726},
isbn={978-989-758-423-7},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - A Literature Review of Recommender Systems for the Cultural Sector
SN - 978-989-758-423-7
AU - Dam N.
AU - Dinh T.
PY - 2020
SP - 715
EP - 726
DO - 10.5220/0009337807150726