Exploratorní analýza životního cyklu firem
| Thesis title in Czech: | Exploratorní analýza životního cyklu firem |
|---|---|
| Thesis title in English: | Exploratory Analysis of Life Cycle of Companies |
| Key words: | životní cyklus firmy|exploratorní analýza|podobnost časových řad |
| English key words: | life cycle of a company|exploratory analysis|similarity of time series |
| Academic year of topic announcement: | 2020/2021 |
| Thesis type: | diploma thesis |
| Thesis language: | |
| Department: | Department of Software Engineering (32-KSI) |
| Supervisor: | doc. RNDr. Irena Holubová, Ph.D. |
| Author: | hidden - assigned and confirmed by the Study Dept. |
| Date of registration: | 25.05.2021 |
| Date of assignment: | 26.05.2021 |
| Confirmed by Study dept. on: | 02.06.2021 |
| Guidelines |
| The aim of the thesis is to explore the Business Register, together with other related open data sources (e.g., inspections of the Czech Trade Inspection Authority, the Register of Contracts etc.), and choose resources suitable for identification of key events in the life cycle of companies. Next, similarity metrics suitable for comparing sequences of events of this type will be compared in order to find the optimal approach for this use case. The identified clusters will be further explored and analysed with regards to various criteria (e.g., business areas, geolocation, time eras, known key political/environmental changes etc.). The general aim is to find interesting business segments, their characteristics and behavioural patterns applicable in understanding and predicting future evolution of various business domains. |
| References |
| http://www.obchodnirejstrik.cz/
https://www.coi.cz/pro-spotrebitele/otevrena-data/kontroly/ https://smlouvy.gov.cz/ Cassisi, C. et al. : Similarity Measures and Dimensionality Reduction Techniques for Time Series Data Mining . Advances in Data Mining Knowledge Discovery and Applications, 2012. http://dx.doi.org/10.5772/49941 El Kader, S.A. et al.: Modeling and Publishing French Business Register (Sirene) Data as Linked Data Using the euBusinessGraph Ontology. SAWSemStats@ISWC 2019. |