František Dařena

• Ph.D.
• Professor (Associate) at Mendel University in Brno

This paper explores the potential of using machine-generated descriptions to characterize a place in a way that humans can identify it. It presents a hybrid approach for generating place descriptions by combining rule-based generation of spatial relation facts with a LLM that converts these facts into natural language descriptions. The study focuse...

Globalization and growing business dynamics lead to weakly harmonized supply chain (SC) systems. While smart technology offers innovation opportunities, supply chains often lack the integration needed to fully leverage resources and collaboration. A comprehensive systems engineering (SE)-driven model for integrated innovation and optimization of sm...

The paper presents a novel method for processing information with a spatial component or querying geospatial databases. It proposes an interactive toponym disambiguation method tailored especially for dialogue systems and chatbots. The method exploits the interactive nature of dialogues to resolve ambiguity by using dialogue clarification technique...

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 decades for balancing exploration and exploitation activities of digital transformation has risen. Still, the desired integrat...

Every larger organisation must establish a set of normative documents to control its processes and describe solutions to common problems. These documents are usually formally written and hard to read. This leads to the necessity of different customer services. Nowadays, a lot of companies are developing chatbots to automate first-line customer supp...

Purpose Current possibilities of accessing business data by regular users usually involve complicated user interfaces or require technical expertise. This results in situations when business owners are separated from their data. The aim of this research is to apply an innovative approach leveraging conversational interfaces to tackle this problem....

The lifetime and complexity of some IT scenarios significantly exceed the typical lifetime and complexity of a technological system. This is a source of significant economic efficiency improvement. In this paper, we propose an approach that enables us to leverage costs, reduce the space floor requirements, and lower CO2 emissions incurred by the in...

A lot of research has been focusing on incorporating online data into models of various phenomena. The chapter focuses on one specific problem coming from the domain of capital markets where the information contained in online environments is quite topical. The presented experiments were designed to reveal the association between online texts (from...

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 method for chatbot platform evaluation. To describe the current state of chatbot platforms, two high-level approaches to chatbot pl...

Crowdfunding as a specific type of crowdsourcing is a method of collecting many rather small monetary contributions to finance or capitalize an enterprise or a particular product. In our paper, we focus on social and affective factors influencing peoples' behaviour in the environment of crowdfunding financing. We model a probability of getting fund...

A lot of research has been focusing on incorporating online data into models of various phenomena. The chapter focuses on one specific problem coming from the domain of capital markets where the information contained in online environments is quite topical. The presented experiments were designed to reveal the association between online texts (from...

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 in documents and are shared across a document collection. We describe the process of discovering the topics, the creation of a...

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 and changes of the S&P 500 stock index. The index values and documents were divided into time windows according to the direction...

The paper presents the result of experiments that were designed with the goal of revealing the association between texts published in online environments (Yahoo! Finance, Facebook, and Twitter) and changes in stock prices of the corresponding companies at a micro level. The association between lexicon detected sentiment and stock price movements wa...

This research addresses a well-known problem in the area of text mining: The high computational complexity caused by many irrelevant features (terms, words), which may play an appreciable role of noise from the classification point of view and non-linearly rule the time and memory requirements. Using a set of real-world textual documents represente...

The Google service delivered a breakthrough customer experience. It has not been neces- sary to browse through a large catalogue of web pages to find a company solving a partic- ular problem. The user just simply wrote a plain question and received related sources. The service understood users’ requests. Later there came personal assistants like Si...

The automated categorization of unstructured textual documents according to their semantic contents plays important role particularly linked with the ever growing volume of such data originating from the Internet. Having a sufficient number of labeled examples, a suitable supervised machine learningbased classifier can be trained. When no labeling...

The chapter introduces clustering as a family of algorithms that can be successfully used to organize text documents into groups without prior knowledge of these groups. The chapter also demonstrates using unsupervised clustering to group large amount of unlabeled textual data (customer reviews written informally in five natural languages) so it ca...

Opinions provided by people that used some services or purchased some goods are a rich source of knowledge. The opinion classification, applying mostly supervised classifiers, is one of the essential tasks. Computer’s technological capabilities are still a major obstacle, especially when processing huge volumes of data. This study proposes and eval...

The paper presents a procedure that helps in revealing topics hidden in large collections of textual documents (such as customer reviews) related to a certain group of products or services. Together with identification of the groups containing the topics the lists of important expressions is presented which helps in understanding what characterizes...

The presented research deals with analyzing continuous streams of textual data written in natural languages. One of problems is revealing possible significant concept changes in Internet blogs, discussions, etc., together with discovering what represents such data, if it is more-or-less topically invariable or changing, and what kind of change occu...

The article describes a method focused on the automatic analysis of large collections of short Internet textual documents, freely written in various natural languages and represented as sparse vectors, to reveal what multi-word phrases are relevant in relation to a given basic categorization. In addition, the revealed phrases serve for discovering...

The paper focuses on preprocessing techniques application to short informal textual documents created in different natural languages. The goal is to evaluate the impact on the quality of the results and computational complexity of the text mining process designed to reveal knowledge hidden in the data. Extensive number of experiments were carried o...

Language-that is, oral or written content that references abstract concepts in subtle ways-is what sets us apart as a species, and in an age defined by such content, language has become both the fuel and the currency of our modern information society. This has posed a vexing new challenge for linguists and engineers working in the field of language...

The automated categorization of unstructured textual documents according to their semantic contents plays important role particularly linked with the ever growing volume of such data originating from the Internet. Having a sufficient number of labeled examples, a suitable supervised machine learningbased classifier can be trained. When no labeling...

The chapter introduces clustering as a family of algorithms that can be successfully used to organize text documents into groups without prior knowledge of these groups. The chapter also demonstrates using unsupervised clustering to group large amount of unlabeled textual data (customer reviews written informally in five natural languages) so it ca...

Gaining new and keeping existing clients or customers can be well-supported by creating and monitoring feedbacks: “Are the customers satisfied? Can we improve our services?” One of possible feedbacks is allowing the customers to freely write their reviews using a simple textual form. The more reviews that are available, the better knowledge can be...

Measuring the quality of products or services, a challenging task is to reveal clients’ satisfaction or sentiment. As people have many opportunities to express their opinions using various on-line channels (e.g., discussions, microblogs, social networks), the question is whether such data might be used for this purpose. Information hidden in the da...

Nowadays, thanks to integration of information and communication technologies to everyday life, huge volumes of information generated by different kinds of subjects emerge. This information might be a valuable source for decision support in many domains of business, political and personal spatial activities. One of such sources is microblog system...

The presented novel procedure named SuDoC – or Semi-unsupervised Document Classification – provides an alternative method to standard clustering techniques when it is necessary to separate a very large set of textual instances into groups that represent the text-document semantics. Unlike the conventional clustering, SuDoC proceeds from an initial...

The presented work deals with automatic detection of semantic contents of groups of textual documents, which are freely written in various natural languages. The large original set of untagged documents is split between a requested number of clusters according to a user’s needs. Each cluster is taken as a class and a classifier (decision tree) is i...

The paper focuses on retrieval of relevant documents written in a natural language based on availability of several candidate examples which are used as the basis for the automatic selection of only items that are similar to these predefined patterns. Presented approach should face problems related to processing user created content in natural lang...

Gaining new and keeping existing clients or customers can be well-supported by creating and monitoring feedbacks: "Are the customers satisfied? Can we improve our services?" One of possible feedbacks is allowing the customers to freely write their reviews using a simple textual form. The more reviews that are available, the better knowledge can be...

Among one of the current and most topical tasks in the area of textual documents processing belongs the problem of automatic categorization. Clustering as the most common form of unsupervised learning enables automatic grouping of unlabeled documents into subsets called clusters. In this paper, the authors are concerned with results of clustering o...

Having a very large volume of unstructured text documents representing different opinions without knowing which document belongs to a certain category, clustering can help reveal the classes. The presented research dealt with almost two millions of opinions concerning customers' (dis)satisfaction with hotel services all over the world. The experime...

Today, the demand for creating a systematic approach for managing sales, ordering, and logistics has increased. Supply Chain Management (SCM) is one of the responses to problems that have arose with the need for managing complex supply chains. Nowadays, most of the activities of Supply Chain Management is realized or supported with computing techno...

Revealing an opinion hidden in a text document is a challenging task. The article presents a method based on the automatic extraction of expressions that are significant for specifying a document attitude to a given topic. The significant expressions are composed using revealed significant words in the documents. The significant words are selected...

Opinions expressed by text documents freely written in various natural languages represent a valuable source of knowledge that is hidden in large datasets. The presented research describes a text mining-method how to discover words that are significant for expressing different opinions (positive and negative). The method applies a simple but unifie...

TROUSSOV, A., DARENA, F., ŽIZKA, J., PARRA, D., BRUSILOVSKY, P.: Vectorised Spreading Activation Algorithm for Centrality Measurement. Spreading Activation is a family of graph-based algorithms widely used in areas such as information retrieval, epidemic models, and recommender systems. In this paper we introduce a novel Spreading Activation (SA) m...

Importance of information systems in supporting business activities and managerial decision making is growing. Decisions related to selecting a suitable information system, including the technological background, human resources, procedures and information belong to one of the most difficult and most responsible ones. As in the case of other types...

This research was inspired by the procedures that are used by human bibliographic searchers: Given some textual, only 'positive' (interesting) examples, coming from one category find the most similar ones that belong to a relevant topic. The problem of categorization of unlabeled relevant and irrelevant textual documents is here solved by using a s...

Due to the rapid spread of computer technologies into day-to-day lives many purchases or purchaserelated decisions are made in the electronic environment of the Web. In order to handle information overload that is the result of the availability of many web-based stores, products and services, consumers use decision support aids that help with need...

This research was inspired by procedures that are used by human bibliographic searchers: Given some textual and only 'positive' (relevant, interesting) examples coming just from one category, find promptly and simply in an available collection of various unlabeled documents the most similar ones that belong to a relevant topic defined by an applica...

Automatic formation of dictionaries containing words significant for expressing different customers' opinions written in natural languages is demonstrated. The research used very large real-world data concerning the hotel accommodation booking via the Internet. The hotel companies could be interested in characteristic words expressing positive and...

The paper investigates a problem connected with automatic analysis of sentiment (opinion) in textual natural-language documents. The initial situation works on the assumption that a user has many documents centered around a certain topic with different opinions of it. The user wants to pick out only relevant documents that represent a certain senti...

The social-network formation and analysis is nowadays one of objects that are in a focus of intensive research. The objective of the paper is to suggest the perspective of representing social networks as graphs, with the application of the graph theory to problems connected with studying the networklike structures and to study spreading activation...

As a consequence of a rapidly changing environment, the success of organizations is dependent upon the ongoing and immediate adjustments of their information systems as reactions to these changes. Therefore, flexibility becomes one of the most crucial features in information systems. This paper specifies a data model oriented framework for the deve...

Customer Relationship Management (CRM) is seen as a holistic framework for interaction of organizations with their customers. It is focused on gaining customers loyalty through providing the value positively perceived by the customers and usually incorporates information and communication technologies in the form of CRM systems. The paper discusses...

The paper is focused on study of information systems that can be applied in the process of marketing planning. General terms from information systems theory are examined from marketing perspective, particular examples of marketing activities support are identified on the basis of literature review and global structure of the Marketing Information S...

In today's dynamically changing environment marketing has a significant role. Creating successful marketing strategies requires large amount of high quality information of various kinds and data types. A powerful database management system is a necessary condition for marketing strategies creation support. The paper briefly describes the field of m...

In the paper an approach to support of strategic management process using the Balanced Scorecard method is discussed. The main focus is primarily directed to the customer perspective as the most important determining factor of today‘s strategic management. The article suggests general framework for construction of individual performance indicators...

The paper deals with the analysis of current situation on the market of business information systems in the Czech Republic from the point of view of their utilization in marketing strategies creation. Based on requirements on marketing information system the structure of these systems and possibilities of their usage are evaluated. It is also point...

Abstrakt Ústav marketingu a obchodu PEF MZLU v Brně se v rámci své výzkumné činnosti zabývá mimo jiné zjišťováním spokojenosti zákazníka. Tyto aktivity bývají prováděny jak zaměstnanci, tak studenty v rámci jejich závěrečných prací. Cílem práce bylo poskytnout nástroj, který by všechny potřebné vý-počty provedl automaticky s co nejmenšími nároky na...

Abstrakt Příspěvek popisuje službu výpočtu indexu spokojenosti zákazníka pro účely vý-zkumu a výuky na PEF MZLU v Brně. Obsahuje popis metodiky výpočtu, technologické řešení aplikace a možnosti jejího využití. Klíčová slova: index spokojenosti zákazníka, webová aplikace, XML Abstract The article describes the service of calculating the customer sat...

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