Advanced Recommender Systems by Exploiting Social Networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00112116" target="_blank" >RIV/00216224:14330/19:00112116 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1109/HCC46620.2019.00025" target="_blank" >http://dx.doi.org/10.1109/HCC46620.2019.00025</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/HCC46620.2019.00025" target="_blank" >10.1109/HCC46620.2019.00025</a>

Result language

angličtina

Original language name

Advanced Recommender Systems by Exploiting Social Networks

Original language description

Social networks have become an indispensable part of our lives, which serve as communication channels, social interaction platforms as well as ubiquitous entertainment tools; meanwhile, social networks constantly generate big social media data that create decision complexity and information overload to users. As a result, recommender systems are emerged to suggest personalized and possibly preferred media for the users. However, social networks have extensively enriched the inputs for recommender systems, such as users' social relations, data source credibility, and new social media types. Consequently, this paper is aimed at identifying the crucial factors that can be used to advance recommender systems in social networks. For each factor, this paper discusses the state-of-the-art recommender system research in that aspect, and suggests how to integrate the featured data to build and improve recommender systems for social networks. The paper further proposes a model to integrate the crucial factors and indicates possible application domains for social media recommender systems.

Czech name

—

Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of the IEEE International Conference on Humanized Computing and Communication

ISBN

9781728141251

ISSN

—

e-ISSN

—

Number of pages

8

Pages from-to

118-125

Publisher name

IEEE

Place of publication

Laguna Hills, CA, USA

Event location

Laguna Hills, CA, USA

Event date

Jan 1, 2019

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000525609700017