A Generalized Evaluation Framework for Multimedia Recommender Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00103876" target="_blank" >RIV/00216224:14330/18:00103876 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1142/S1793351X18500046" target="_blank" >http://dx.doi.org/10.1142/S1793351X18500046</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1142/S1793351X18500046" target="_blank" >10.1142/S1793351X18500046</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A Generalized Evaluation Framework for Multimedia Recommender Systems

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

A Generalized Evaluation Framework for Multimedia Recommender Systems

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

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 periodika

International Journal of Semantic Computing

ISSN

1793-351X

e-ISSN

—

Svazek periodika

12

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

17

Strana od-do

541-557

Kód UT WoS článku

000453524500005

EID výsledku v databázi Scopus

2-s2.0-85058781460