GE, Mouzhi and Fabio PERSIA. Evaluation in Multimedia Recommender Systems: A Practical Guide. In Proceedings of the 12th IEEE International Conference on Semantic Computing. California, USA: IEEE, 2018, p. 294-297. ISBN 978-1-5386-4407-2. Available from: https://dx.doi.org/10.1109/ICSC.2018.00050.
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Basic information
Original name Evaluation in Multimedia Recommender Systems: A Practical Guide
Name in Czech Evaluation in Multimedia Recommender Systems: A Practical Guide
Authors GE, Mouzhi (156 China, guarantor, belonging to the institution) and Fabio PERSIA (380 Italy).
Edition California, USA, Proceedings of the 12th IEEE International Conference on Semantic Computing, p. 294-297, 4 pp. 2018.
Publisher IEEE
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14330/18:00102282
Organization unit Faculty of Informatics
ISBN 978-1-5386-4407-2
ISSN 2325-6516
Doi http://dx.doi.org/10.1109/ICSC.2018.00050
UT WoS 000450112200045
Keywords in English Multimedia Recommender Systems; Evaluation Criteria; Media Technologies
Tags core_B, firank_B
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 29/4/2019 06:38.
Abstract
With the widespread availability of media technologies, such as real-time streaming, new IoT devices and smartphones, multimedia data are extensively increased and the big multimedia data are rapidly spreaded over various social networks. Thus, different multimedia recommender systems have been emerging to help users select the useful multimedia objects. However, due to distinct features of multimedia objects, it is difficult to conduct a proper evaluation for the multimedia recommender systems, and the evaluation from the general recommender systems might not be totally adopted to evaluate them. In this paper, we therefore review and analyze the evaluation criteria that are used in the previous multimedia recommender system papers. Based on the review, we propose a set of the practical advices to lead practitioners and researchers to perform evaluations for multimedia recommender systems.
PrintDisplayed: 25/4/2024 08:59