NLP Technologies and AI for business: applications and methods utilized to reduce costs and workflow improvement
| Thesis title: | NLP Technologies and AI for business: applications and methods utilized to reduce costs and workflow improvement |
|---|---|
| Author: | Staroverova, Ekaterina |
| Thesis type: | Diploma thesis |
| Supervisor: | Potančok, Martin |
| Opponents: | Zimmermann, Pavel |
| Thesis language: | English |
| Abstract: | The aim of the thesis is to select and implement NLP technologies, AI frameworks and applications that are able to influence and benefit business purposes and processes for certain cases (such as the proposal for HR, Procurement, Sales divisions) based on investigation and revealing of processes flows in existed workflows and business organization. |
| Keywords: | NLP; AI; Chatbot; Mailbot; ML; BERT; Azure ML |
| Thesis title: | NLP Technologies and AI for business: applications and methods utilized to reduce costs and workflow improvement |
|---|---|
| Author: | Staroverova, Ekaterina |
| Thesis type: | Diplomová práce |
| Supervisor: | Potančok, Martin |
| Opponents: | Zimmermann, Pavel |
| Thesis language: | English |
| Abstract: | The aim of the thesis is to select and implement NLP technologies, AI frameworks and applications that are able to influence and benefit business purposes and processes for certain cases (such as the proposal for HR, Procurement, Sales divisions) based on investigation and revealing of processes flows in existed workflows and business organization. |
| Keywords: | AI; Chatbot; NLP; Mailbot; ML; BERT; Azure ML |
Information about study
| Study programme: | Aplikovaná informatika/Information Systems Management |
|---|---|
| Type of study programme: | Magisterský studijní program |
| Assigned degree: | Ing. |
| Institutions assigning academic degree: | Vysoká škola ekonomická v Praze |
| Faculty: | Faculty of Informatics and Statistics |
| Department: | Department of Information Technologies |
Information on submission and defense
| Date of assignment: | 12. 8. 2020 |
|---|---|
| Date of submission: | 19. 6. 2021 |
| Date of defense: | 25. 8. 2021 |
| Identifier in the InSIS system: | https://insis.vse.cz/zp/73794/podrobnosti |