| Title |
Big data processing system for Lithuania economic activity nowcasting / |
| Authors |
Lukauskas, Mantas ; Pilinkienė, Vaida ; Bruneckienė, Jurgita ; Stundžienė, Alina ; Grybauskas, Andrius ; Ruzgas, Tomas |
| DOI |
10.15388/DAMSS.13.2022 |
| ISBN |
9786090707944 |
| eISBN |
9786090707951 |
| Full Text |
|
| Is Part of |
DAMSS 2022: 13th conference on data analysis methods for software systems, Druskininkai, Lithuania, December 1–3, 2022 / Lithuanian computer society, Vilnius university Institute of data science and digital technologies, Lithuanian academy of sciences.. Vilnius : Vilnius university press, 2022. p. 55.. ISBN 9786090707944. eISBN 9786090707951 |
| Abstract [eng] |
The assessment of economic activity is an important assessment of the state’s economy, which allows assessing the current situation, as well as predicting future prospects. The increasing amount of data every year allows this data to be used in the forecasting of economic processes. However, due to the large amount of data, its rapid renewal, and its diversity, it is difficult to evaluate it in traditional ways. Traditional methods of assessing economic activity use monthly or quarterly data, which are no longer appropriate in the face of various economic shocks. A good example of this is the COVID-19 pandemic or the war in Ukraine, which affects the state’s economy quite quickly. For this reason, it becomes important to evaluate not only traditional economic indicators, but also various alternative ones collected from various openly available sources. The purpose of this work is to present a possible economic activity assessment system that collects, processes, transforms and visualizes Lithuanian economic activity. The developed economic activity forecasting system allows you to automatically collect text information, prices of products and services, real estate and others. And using machine learning methods, this data is turned into valuable insights, which can be used in state, business and other decision-making. |
| Published |
Vilnius : Vilnius university press, 2022 |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2022 |
| CC license |
|
