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Pregled bibliografske jedinice broj: 1189522

A Novel Method for IPTV Customer Behavior Analysis Using Time Series


Hlupic, Tomislav; Orescanin, Drazen; Baranovic, Mirta
A Novel Method for IPTV Customer Behavior Analysis Using Time Series // IEEE Access, 10 (2022), 37003-37015 doi:10.1109/access.2022.3164409 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1189522 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
A Novel Method for IPTV Customer Behavior Analysis Using Time Series

Autori
Hlupic, Tomislav ; Orescanin, Drazen ; Baranovic, Mirta

Izvornik
IEEE Access (2169-3536) 10 (2022); 37003-37015

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
IPTV, time series analysis, data analysis, user behavior analysis, time series similarity, user proling

Sažetak
Internet Protocol Television (IPTV) has had a significant impact on live TV content consumption in the past decade, as improvements in the broadband speed have allowed more data volume to be delivered. In addition to existing infrastructure, which is mostly based on the set top boxes, new content providers have emerged, utilizing newly developed proprietary streaming platforms. As the number of IPTV users grew, more volume and variety of data became available for analysis. By analyzing stored user actions, it is possible to create a multivariate time series that represents user behavior over time. The approach presented in the paper is based on multivariate time series generation from user data and determining the similarity between them. Time series are created for each user based on the proposed quantified action sets, grouped in the feature groups and summarized over time. The action sets and feature groups can be adjusted to a certain IPTV platform. The end result of the analysis is the similarity score matrix, generated by calculating the similarities of all users' time series, where the similarity measure calculation can be chosen arbitrarily.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Poveznice na cjeloviti tekst rada:

doi ieeexplore.ieee.org

Citiraj ovu publikaciju:

Hlupic, Tomislav; Orescanin, Drazen; Baranovic, Mirta
A Novel Method for IPTV Customer Behavior Analysis Using Time Series // IEEE Access, 10 (2022), 37003-37015 doi:10.1109/access.2022.3164409 (međunarodna recenzija, članak, znanstveni)
Hlupic, T., Orescanin, D. & Baranovic, M. (2022) A Novel Method for IPTV Customer Behavior Analysis Using Time Series. IEEE Access, 10, 37003-37015 doi:10.1109/access.2022.3164409.
@article{article, author = {Hlupic, Tomislav and Orescanin, Drazen and Baranovic, Mirta}, year = {2022}, pages = {37003-37015}, DOI = {10.1109/access.2022.3164409}, keywords = {IPTV, time series analysis, data analysis, user behavior analysis, time series similarity, user proling}, journal = {IEEE Access}, doi = {10.1109/access.2022.3164409}, volume = {10}, issn = {2169-3536}, title = {A Novel Method for IPTV Customer Behavior Analysis Using Time Series}, keyword = {IPTV, time series analysis, data analysis, user behavior analysis, time series similarity, user proling} }
@article{article, author = {Hlupic, Tomislav and Orescanin, Drazen and Baranovic, Mirta}, year = {2022}, pages = {37003-37015}, DOI = {10.1109/access.2022.3164409}, keywords = {IPTV, time series analysis, data analysis, user behavior analysis, time series similarity, user proling}, journal = {IEEE Access}, doi = {10.1109/access.2022.3164409}, volume = {10}, issn = {2169-3536}, title = {A Novel Method for IPTV Customer Behavior Analysis Using Time Series}, keyword = {IPTV, time series analysis, data analysis, user behavior analysis, time series similarity, user proling} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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