Pregled bibliografske jedinice broj: 1219603
Predicting TV Viewership with Regression Models
Predicting TV Viewership with Regression Models // 7th International Conference on Smart and Sustainable Technologies (SpliTech)
Bol, Hrvatska; Split, Hrvatska: Institute of Electrical and Electronics Engineers (IEEE), 2022. str. 1-7 doi:10.23919/splitech55088.2022.9854230 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1219603 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Predicting TV Viewership with Regression Models
Autori
Seric, Ljiljana ; Miletic, Dino ; Ivanda, Antonia ; Braovic, Maja
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
ISBN
978-1-6654-8828-0
Skup
7th International Conference on Smart and Sustainable Technologies (SpliTech)
Mjesto i datum
Bol, Hrvatska; Split, Hrvatska, 05.07.2022. - 08.07.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
regression model, predicting TV viewership, LSTM network, neural network, time series prediction
Sažetak
In this paper were analyzed the applicability of regression models to the problem of real time viewership prediction. In this paper the analysis is based on precise viewership data obtained from the national company responsible for maintaining the broadcasting infrastructure. The viewership data and the TV schedule archive data were preprocessed to create a dataset on which the analysis is performed. Analysis was performed on the correlation of the number of viewers with time series trends and TV schedule features. The results were compared with several implemented and trained models, and compared with the performance of various tested models. In this paper is described the methodology of building the models and discussed the obtained results.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Temeljne tehničke znanosti
