Pregled bibliografske jedinice broj: 1145538
Investigating Singular Value Decomposition as a Tool for Data Management in Tourism
Investigating Singular Value Decomposition as a Tool for Data Management in Tourism // Proceedings of the 16th International Symposium on Operational Research in Slovenia, SOR'21 / Drobne, S. ; Zadnik Stirn, L. ; Kljajić Borštar, M. ; Povh, J. ; Žerovnik, J. - Ljubljana : Slovenian Society Informatika (SDI), Section for Operational Research (SOR) / Drobne, Samo ; Zadnik Stirn, Lidija. ; Kljajic Borstnar, Mirjana ; Povh, Janez ; Zerovnik, Janez (ur.).
Ljubljana: Slovensko društvo informatika, 2021. str. 17-22 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1145538 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Investigating Singular Value Decomposition as a Tool
for Data Management in Tourism
Autori
Kekez, Ivan ; Garbin Praničević, Daniela
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 16th International Symposium on Operational Research in Slovenia, SOR'21 / Drobne, S. ; Zadnik Stirn, L. ; Kljajić Borštar, M. ; Povh, J. ; Žerovnik, J. - Ljubljana : Slovenian Society Informatika (SDI), Section for Operational Research (SOR)
/ Drobne, Samo ; Zadnik Stirn, Lidija. ; Kljajic Borstnar, Mirjana ; Povh, Janez ; Zerovnik, Janez - Ljubljana : Slovensko društvo informatika, 2021, 17-22
ISBN
978-961-6165-57-0
Skup
16th International Symposium on Operational Research (SOR 2021)
Mjesto i datum
Online, 22.09.2021. - 24.09.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
singular value decomposition, tourism, data management, dimensionality reduction
Sažetak
: This paper contains a brief description of a singular value decomposition method as a tool for data management and performance improvement in the context of tourism activities – online hotel ratings. Throughout the paper, the authors introduced elementary linear theory background and SVD mathematical algorithm in a simplified way in order to express its contribution to the analytical value of data. Demonstrated algorithm and achieved results indicate two decisions. To perform high compression despite potential analytical and misinterpretation risks due to the details loss or keeping the data volume, only with minimal reduction for a largely dependent, false, and outlier data
Izvorni jezik
Engleski
Znanstvena područja
Ekonomija
