A Survey of Multimedia Recommender Systems: Challenges and
Opportunities

J 2017

A Survey of Multimedia Recommender Systems: Challenges and Opportunities

GE, Mouzhi a Fabio PERSIA

Základní údaje

Originální název

A Survey of Multimedia Recommender Systems: Challenges and Opportunities

Autoři

GE, Mouzhi (156 Čína, garant, domácí) a Fabio PERSIA

Vydání

International Journal of Semantic Computing, World Scientiﬁc Publishing, 2017, 1793-351X

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Velká Británie a Severní Irsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Kód RIV

RIV/00216224:14330/17:00096837

Organizační jednotka

Fakulta informatiky

DOI

https://doi.org/10.1142/S1793351X17500039

UT WoS

000412119100009

EID Scopus

2-s2.0-85048390804

Klíčová slova anglicky

Multimedia recommender system; multimedia objects; research challenges; multimedia recommendations

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 24. 4. 2018 10:45, doc. Mouzhi Ge, Ph.D.

Anotace

V originále

Multimedia information has been extensively growing from a variety of sources such as cameras or video recorders. In order to select the useful multimedia objects, multimedia recommender system has been emerging as a tool to help users choose which multimedia objects might be interesting for them. However, given the complexity of multimedia objects, it is challenging to provide effective multimedia recommendations. In this paper, we therefore conduct a survey in both the multimedia information system and recommender system communities. We further focus on the works that span the two communities, especially the research on multimedia recommender systems. Based on our review, we propose a set of research challenges, which can be used to implicate the future research directions for multimedia recommender systems. For each research challenge, we have also provided the insights of how to perform the follow-up research.

Citovat

GE, Mouzhi a Fabio PERSIA. A Survey of Multimedia Recommender Systems: Challenges and Opportunities. International Journal of Semantic Computing. World Scientiﬁc Publishing, 2017, roč. 11, č. 3, s. 411-428. ISSN 1793-351X. Dostupné z: https://doi.org/10.1142/S1793351X17500039.

@article{1381909,
   author = {Ge, Mouzhi and Persia, Fabio},
   article_number = {3},
   doi = {https://doi.org/10.1142/S1793351X17500039},
   keywords = {Multimedia recommender system; multimedia objects; research challenges; multimedia recommendations},
   language = {eng},
   issn = {1793-351X},
   journal = {International Journal of Semantic Computing},
   title = {A Survey of Multimedia Recommender Systems: Challenges and Opportunities},
   url = {https://www.worldscientific.com/doi/abs/10.1142/S1793351X17500039},
   volume = {11},
   year = {2017}
}

TY  - JOUR
ID  - 1381909
AU  - Ge, Mouzhi - Persia, Fabio
PY  - 2017
TI  - A Survey of Multimedia Recommender Systems: Challenges and Opportunities
JF  - International Journal of Semantic Computing
VL  - 11
IS  - 3
SP  - 411-428
EP  - 411-428
PB  - World Scientiﬁc Publishing
SN  - 1793351X
KW  - Multimedia recommender system
KW  - multimedia objects
KW  - research challenges
KW  - multimedia recommendations
UR  - https://www.worldscientific.com/doi/abs/10.1142/S1793351X17500039
N2  - Multimedia information has been extensively growing from a variety of sources such as cameras or video recorders. In order to select the useful multimedia objects, multimedia recommender system has been emerging as a tool to help users choose which multimedia objects might be interesting for them. However, given the complexity of multimedia objects, it is challenging to provide effective multimedia recommendations. In this paper, we therefore conduct a survey in both the multimedia information system and recommender system communities. We further focus on the works that span the two communities, especially the research on multimedia recommender systems. Based on our review, we propose a set of research challenges, which can be used to implicate the future research directions for multimedia recommender systems. For each research challenge, we have also provided the insights of how to perform the follow-up research.
ER  -

GE, Mouzhi a Fabio PERSIA. A Survey of Multimedia Recommender Systems: Challenges and Opportunities. \textit{International Journal of Semantic Computing}. World Scientiﬁc Publishing, 2017, roč.~11, č.~3, s.~411-428. ISSN~1793-351X. Dostupné z: https://doi.org/10.1142/S1793351X17500039.

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