GE, Mouzhi and Fabio PERSIA. A Generalized Evaluation Framework for Multimedia Recommender Systems. International Journal of Semantic Computing. World Scientific, 2018, vol. 12, No 4, p. 541-557. ISSN 1793-351X. Available from: https://dx.doi.org/10.1142/S1793351X18500046.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name A Generalized Evaluation Framework for Multimedia Recommender Systems
Authors GE, Mouzhi (156 China, guarantor, belonging to the institution) and Fabio PERSIA (380 Italy).
Edition International Journal of Semantic Computing, World Scientific, 2018, 1793-351X.
Other information
Original language English
Type of outcome Article in a journal
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
RIV identification code RIV/00216224:14330/18:00103876
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1142/S1793351X18500046
UT WoS 000453524500005
Keywords in English Multimedia recommender system; multimedia recommendation; evaluation framework; evaluation criteria
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 29/4/2019 17:24.
Abstract
With the widespread availability of media technologies, such as real-time streaming, new Internet-of-Thing devices and smart phones, multimedia data are extensively increased and the big multimedia data rapidly spread over various social networks. This has created complexity and information overload for users to choose the suitable multimedia objects. Thus, different multimedia recommender systems have been emerging to help users find the useful multimedia objects that are possibly preferred by the user. However, the evaluation of these multimedia recommender systems is still in an ad-hoc stage. Given the distinct features of multimedia objects, the evaluation criteria adopted from the general recommender systems might not be effectively used to evaluate multimedia recommendations. In this paper, we therefore review and analyze the evaluation criteria that have been used in the previous multimedia recommender system papers. Based on the review, we propose a generalized evaluation framework to guide the researchers and practitioners to perform evaluations, especially user-centric evaluations, for multimedia recommender systems.
PrintDisplayed: 18/7/2024 12:36