Click to open the HelpDesk interface
AECE - Front page banner

Menu:


FACTS & FIGURES

JCR Impact Factor: 0.800
JCR 5-Year IF: 1.000
SCOPUS CiteScore: 2.0
Issues per year: 4
Current issue: Feb 2024
Next issue: May 2024
Avg review time: 78 days
Avg accept to publ: 48 days
APC: 300 EUR


PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


TRAFFIC STATS

2,499,866 unique visits
994,668 downloads
Since November 1, 2009



Robots online now
bingbot
Googlebot


SCOPUS CiteScore

SCOPUS CiteScore


SJR SCImago RANK

SCImago Journal & Country Rank




TEXT LINKS

Anycast DNS Hosting
MOST RECENT ISSUES

 Volume 24 (2024)
 
     »   Issue 1 / 2024
 
 
 Volume 23 (2023)
 
     »   Issue 4 / 2023
 
     »   Issue 3 / 2023
 
     »   Issue 2 / 2023
 
     »   Issue 1 / 2023
 
 
 Volume 22 (2022)
 
     »   Issue 4 / 2022
 
     »   Issue 3 / 2022
 
     »   Issue 2 / 2022
 
     »   Issue 1 / 2022
 
 
 Volume 21 (2021)
 
     »   Issue 4 / 2021
 
     »   Issue 3 / 2021
 
     »   Issue 2 / 2021
 
     »   Issue 1 / 2021
 
 
  View all issues  


FEATURED ARTICLE

Application of the Voltage Control Technique and MPPT of Stand-alone PV System with Storage, HIVZIEFENDIC, J., VUIC, L., LALE, S., SARIC, M.
Issue 1/2022

AbstractPlus






LATEST NEWS

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

2021-Jun-30
Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

Read More »


    
 

  1/2014 - 18

 HIGH-IMPACT PAPER 

TV Recommendation and Personalization Systems: Integrating Broadcast and Video On demand Services

SOARES, M. See more information about SOARES, M. on SCOPUS See more information about SOARES, M. on IEEExplore See more information about SOARES, M. on Web of Science, VIANA, P. See more information about VIANA, P. on SCOPUS See more information about VIANA, P. on SCOPUS See more information about VIANA, P. on Web of Science
 
View the paper record and citations in View the paper record and citations in Google Scholar
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (804 KB) | Citation | Downloads: 942 | Views: 4,225

Author keywords
collaborative filtering, content filtering, recommendation systems, TV-Anytime

References keywords
recommendation(6), user(5), systems(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-02-28
Volume 14, Issue 1, Year 2014, On page(s): 115 - 120
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.01018
Web of Science Accession Number: 000332062300018
SCOPUS ID: 84894614863

Abstract
Quick view
Full text preview
The expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations.


References | Cited By

Cited-By Clarivate Web of Science

Web of Science® Times Cited: 8 [View]
View record in Web of Science® [View]
View Related Records® [View]

Updated today


Cited-By SCOPUS

SCOPUS® Times Cited: 14
View record in SCOPUS®
[Free preview]
View citations in SCOPUS® [Free preview]

Updated today

Cited-By CrossRef

[1] Data-driven personalisation of television content: a survey, Nixon, Lyndon, Foss, Jeremy, Apostolidis, Konstantinos, Mezaris, Vasileios, Multimedia Systems, ISSN 0942-4962, Issue 6, Volume 28, 2022.
Digital Object Identifier: 10.1007/s00530-022-00926-6
[CrossRef]

[2] Mass Media Deploying Digital Personalization: An Empirical Investigation, Loebbecke, Claudia, Oberschulte, Franziska, Boboschko, Irina, International Journal on Media Management, ISSN 1424-1277, Issue 3-4, Volume 23, 2021.
Digital Object Identifier: 10.1080/14241277.2022.2038605
[CrossRef]

[3] A Hybrid Approach for Personalized News Recommendation in a Mobility Scenario Using Long-Short User Interest, Viana, Paula, Soares, Márcio, International Journal on Artificial Intelligence Tools, ISSN 0218-2130, Issue 02, Volume 26, 2017.
Digital Object Identifier: 10.1142/S0218213017600120
[CrossRef]

[4] Tuning metadata for better movie content-based recommendation systems, Soares, Márcio, Viana, Paula, Multimedia Tools and Applications, ISSN 1380-7501, Issue 17, Volume 74, 2015.
Digital Object Identifier: 10.1007/s11042-014-1950-1
[CrossRef]

[5] Consumer Attitudes toward News Delivering: An Experimental Evaluation of the Use and Efficacy of Personalized Recommendations, Viana, Paula, Soares, Márcio, Gaio, Rita, Correia, Amilcar, Information, ISSN 2078-2489, Issue 7, Volume 11, 2020.
Digital Object Identifier: 10.3390/info11070350
[CrossRef]

[6] A literature review of recommender systems in the television domain, Véras, Douglas, Prota, Thiago, Bispo, Alysson, Prudêncio, Ricardo, Ferraz, Carlos, Expert Systems with Applications, ISSN 0957-4174, Issue 22, Volume 42, 2015.
Digital Object Identifier: 10.1016/j.eswa.2015.06.052
[CrossRef]

[7] Ontology Matched Cross Domain Personalized Recommendation of Tourist Attractions, Valliyammai, C., Ephina Thendral, S., Wireless Personal Communications, ISSN 0929-6212, Issue 1, Volume 107, 2019.
Digital Object Identifier: 10.1007/s11277-019-06290-5
[CrossRef]

[8] A hybrid recommendation system for news in a mobile environment, Viana, Paula, Soares, Márcio, Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics, ISBN 9781450340564, 2016.
Digital Object Identifier: 10.1145/2912845.2912852
[CrossRef]

[9] The SOM Based Improved K-Means Clustering Collaborative Filtering Algorithm in TV Recommendation System, Ma, Zhaocai, Yang, Yi, Wang, Fei, Li, Caihong, Li, Lian, 2014 Second International Conference on Advanced Cloud and Big Data, ISBN 978-1-4799-8085-7, 2014.
Digital Object Identifier: 10.1109/CBD.2014.45
[CrossRef]

Updated today

Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.

Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.


Copyright ©2001-2024
Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.

Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.

Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.




Website loading speed and performance optimization powered by: 


DNS Made Easy