Pregled bibliografske jedinice broj: 1043936
Predicting the Number of Downloads of Open Datasets by Naïve Bayes Classifier
Predicting the Number of Downloads of Open Datasets by Naïve Bayes Classifier // TEM Journal, 8 (2019), 4; 1331-1338 doi:10.18421/TEM84-33 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1043936 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Predicting the Number of Downloads of Open Datasets by Naïve Bayes Classifier
Autori
Šlibar, Barbara
Izvornik
TEM Journal (2217-8309) 8
(2019), 4;
1331-1338
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Dataset Characteristics ; Naïve Bayes Classifier ; Open Data
Sažetak
Nowadays, the use of Open Data has become more common and prominent, but there are a lot of questions regarding its quality. Most of the revised researches deal with the quality of Open Data portals, rather than estimation of the open datasets quality. Therefore, the main idea of this research is lowering to the level of the dataset itself in order to assess how much such data is downloaded by end users of Open Data portals on the basis of general dataset characteristics. A model for predicting the number of downloads of open datasets based on their general characteristics was constructed using the Naïve Bayes Classifier. Based on the obtained results, it is discussed if the certain dataset character is good predictor of open dataset downloading and to what extent.
Izvorni jezik
Engleski
POVEZANOST RADA
Ustanove:
Fakultet organizacije i informatike, Varaždin
Profili:
Barbara Šlibar
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Emerging Sources Citation Index (ESCI)
- Scopus
