Research Challenges in Multimedia Recommender Systems

D 2017

Research Challenges in Multimedia Recommender Systems

GE, Mouzhi and Fabio PERSIA

Basic information

Original name

Research Challenges in Multimedia Recommender Systems

Authors

GE, Mouzhi (156 China, guarantor, belonging to the institution) and Fabio PERSIA (380 Italy)

Edition

San Diego, USA, Proceedings of the IEEE International Conference on Semantic Computing, p. 344-347, 4 pp. 2017

Publisher

IEEE

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

IEEE, CORE B Conference, SCOPUS, WoS, DBLP

RIV identification code

RIV/00216224:14330/17:00096405

Organization unit

Faculty of Informatics

ISBN

978-1-5090-4896-0

DOI

http://dx.doi.org/10.1109/ICSC.2017.31

UT WoS

000403391300065

Keywords in English

Multimedia Recommendation; Multimedia Recommender Systems; Research Challenges

Abstract

V originále

Nowadays, since multimedia information has been extensively growing from a variety of sources, such photos from social networks, unstructured text from different websites, or raw video feed from digital sensors, 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, it is still challenging to provide effective recommendations, and research so far could only address limited aspects. Therefore, in this paper 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 to explain which aspects are worth further investigation.

Citovat

GE, Mouzhi and Fabio PERSIA. Research Challenges in Multimedia Recommender Systems. Online. In Proceedings of the IEEE International Conference on Semantic Computing. San Diego, USA: IEEE, 2017, p. 344-347. ISBN 978-1-5090-4896-0. Available from: https://dx.doi.org/10.1109/ICSC.2017.31.

@inproceedings{1377091,
   author = {Ge, Mouzhi and Persia, Fabio},
   address = {San Diego, USA},
   booktitle = {Proceedings of the IEEE International Conference on Semantic Computing},
   doi = {http://dx.doi.org/10.1109/ICSC.2017.31},
   keywords = {Multimedia Recommendation; Multimedia Recommender Systems; Research Challenges},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {San Diego, USA},
   isbn = {978-1-5090-4896-0},
   pages = {344-347},
   publisher = {IEEE},
   title = {Research Challenges in Multimedia Recommender Systems},
   url = {http://icsc.eecs.uci.edu},
   year = {2017}
}

TY  - JOUR
ID  - 1377091
AU  - Ge, Mouzhi - Persia, Fabio
PY  - 2017
TI  - Research Challenges in Multimedia Recommender Systems
PB  - IEEE
CY  - San Diego, USA
SN  - 9781509048960
KW  - Multimedia Recommendation
KW  - Multimedia Recommender Systems
KW  - Research Challenges
UR  - http://icsc.eecs.uci.edu
N2  - Nowadays, since multimedia information has been extensively growing from a variety of sources, such photos from social networks, unstructured text from different websites, or raw video feed from digital sensors, 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, it is still challenging to provide effective recommendations, and research so far could only address limited aspects. Therefore, in this paper 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 to explain which aspects are worth further investigation.
ER  -

GE, Mouzhi and Fabio PERSIA. Research Challenges in Multimedia Recommender Systems. Online. In \textit{Proceedings of the IEEE International Conference on Semantic Computing}. San Diego, USA: IEEE, 2017, p.~344-347. ISBN~978-1-5090-4896-0. Available from: https://dx.doi.org/10.1109/ICSC.2017.31.

Detailed Information on Publication Record