Browsing by Author "Dařena, František"

Now showing items 1-5 of 5

    • Activating supply chain business models' value potentials through Systems Engineering 

      Nürk, Jochen; Dařena, František (John Wiley & Sons, Inc., 2023)
      New business opportunities, driven by smart digitalization technology and initiatives such as Industry 4.0, significantly change business models and their innovation rate. The complexity of methodologies developed in recent ...

    • Analysis of the Association Between Topics in Online Documents and Stock Price Movements 

      Dařena, František; Přichystal, Jan (Mendelova univerzita v Brně, 2018)
      This paper aims at discovering the topics hidden in the newspaper articles that have an impact on movements of stock prices of the corresponding companies. Document topics are characterized by combinations of specific words ...

    • Chatbots for enterprises: Outlook 

      Kostelník, Pavel; Pisařovic, Ivo; Muroň, Mikuláš; Dařena, František; Procházka, David (Mendelova univerzita v Brně, 2019)
      Chatbots are going to be the main tool for automated conversations with customers. Still, there is no consistent methodology for choosing a suitable chatbot platform for a particular business. This paper proposes a new ...

    • Quality of Word Vectors and Its Impact on Named Entity Recognition in Czech 

      Dařena, František; Süss, Martin (Mendelova univerzita v Brně, 2020)
      Named Entity Recognition (NER) focuses on finding named entities in text and classifying them into one of the entity types. Modern state-of-the-art NER approaches avoid using hand-crafted features and rely on feature-inferring ...

    • Text-Mining in Streams of Textual Data Using Time Series Applied to Stock Market 

      Netolický, Pavel; Petrovský, Jonáš; Dařena, František (Mendelova univerzita v Brně, 2018)
      Each day, a lot of text data is generated. This data comes from various sources and may contain valuable information. In this article, we use text mining methods to discover if there is a connection between news articles ...