How to exploit Recommender Systems in Social Media

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00103078" target="_blank" >RIV/00216224:14330/18:00103078 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/IRI.2018.00085" target="_blank" >http://dx.doi.org/10.1109/IRI.2018.00085</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IRI.2018.00085" target="_blank" >10.1109/IRI.2018.00085</a>

Jazyk výsledku

angličtina

Název v původním jazyce

How to exploit Recommender Systems in Social Media

Popis výsledku v původním jazyce

The rapid increase and widespread of social media data have created new research challenges and opportunities for social media recommender systems, which are designed to recommend personalized, interesting, credible social media content with possible social impact. However, due to complexity in social network and new media interaction, the research of social media recommender systems is still on its initial stage. Therefore, this paper aims to review the state-of-the-art research that are related to social media recommender systems, and identify the critical factors for building new social media recommender systems. Our results show that relevance, validity, popularity, credibility and social impact are considered to be the 5 important factors for social media recommender systems.

Název v anglickém jazyce

How to exploit Recommender Systems in Social Media

Popis výsledku anglicky

The rapid increase and widespread of social media data have created new research challenges and opportunities for social media recommender systems, which are designed to recommend personalized, interesting, credible social media content with possible social impact. However, due to complexity in social network and new media interaction, the research of social media recommender systems is still on its initial stage. Therefore, this paper aims to review the state-of-the-art research that are related to social media recommender systems, and identify the critical factors for building new social media recommender systems. Our results show that relevance, validity, popularity, credibility and social impact are considered to be the 5 important factors for social media recommender systems.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the IEEE 19th International Conference on Information Reuse and Integration for Data Science

ISBN

9781538626597

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

537-541

Název nakladatele

IEEE

Místo vydání

Salt Lake City

Místo konání akce

Salt Lake City, Utah, USA

Datum konání akce

1. 1. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000442457000077