Gintautas Dzemyda

Vilnius University · Institute of Data Science and Digital Technologies

Fraudulent transaction data tend to have several categorical features with high cardinality. It makes data preprocessing complicated if categories in such features do not have an order or meaningful mapping to numerical values. Even though many encoding techniques exist, their impact on highly imbalanced massive data sets is not thoroughly evaluate...

Fraud detection is a system that prevents criminals from obtaining financial assets. The research aims to increase machine learning prediction quality on fraudulent cases as well as decrease false positive and false negative cases in prediction. Fraudulent data like credit card transactions are usually imbalanced data, and standard machine learning...

Humans tend to systematically underestimate exponential growth and perceive it in linear terms, which can have severe consequences in a variety of fields. Recent studies attempted to examine the origins of this bias and to mitigate it by using the logarithmic vs. the linear scale in graphical representations. However, they yielded conflicting resul...

Fraud is an illegal action by someone who wants to gain financial benefit from another person or institution. It has evident economic consequences on private enterprises, public services, and individuals’ financial situation. Fraudulent activity is constantly evolving - it has no persistent patterns. Machine learning is one of the ways to solve fra...

Safe navigation at sea is more important than ever. Cargo is usually transported by vessel because it makes economic sense. However, marine accidents can cause huge losses of people, cargo, and the vessel itself, as well as irreversible ecological disasters. These are the reasons to strive for safe vessel navigation. The navigator shall ensure safe...

Multidimensional scaling (MDS) is a widely used technique for mapping data from a high-dimensional to a lower-dimensional space and for visualizing data. Recently, a new method, known as Geometric MDS, has been developed to minimize the MDS stress function by an iterative procedure, where coordinates of a particular point of the projected space are...

Multidimensional scaling (MDS) is an often-used method to reduce the dimensionality of multidimensional data nonlinearly and to present the data visually. MDS minimizes some stress function which variables are coordinates of points in the projected lower-dimensional space. Recently, the so-called Geometric MDS has been developed, where the stress f...

The conference "Lithuanian MSc Research in Informatics and ICT" is a venue to present research of Lithuanian MSc theses in informatics and ICT. The aim of the event is to raise skills of MSc and other students, familiarize themselves with the research of other students, encourage their interest in scientific activities. Students from Kaunas Univers...

A well-known and widely used technique for mapping data from high-dimensional space to lower-dimensional space is multidimensional scaling (MDS). Although MDS, as a dimensionality reduction method used for data visualization, demonstrates great versatility, it is computationally demanding, especially when the data set is not fixed and its size is c...

Machine learning is compelling in solving various applied problems. Nevertheless, machine learning methods lack the contextual reasoning capabilities and cannot be fitted to utilize additional information about circumstances, environments, backgrounds, etc. Such information provides essential knowledge about possible reasons for particular actions....

The conference "Lithuanian MSc Research in Informatics and ICT" is a venue to present research of Lithuanian MSc theses in informatics and ICT. The aim of the event is to raise skills of MSc and other students, familiarize themselves with the research of other students, encourage their interest in scientific activities. Students from Kaunas Univers...

Nowadays, it is vital to ensure safe vessel navigation. As in the old days, this responsibility lies on the marine navigator. The main issue to provide safety is to plan and predict the vessel maneuvering in the massive congestion. The enormous permanent stream of marine traffic data is tricky to process for vessel navigator. Thus, the main reason...

Multidimensional scaling (MDS) is a prevalent method for presenting multidimensional data visually. MDS minimizes some stress function. We have proposed in [1] and [2] to consider the stress function and multidimensional scaling, in general, from the geometric point of view, and the so-called Geometric MDS has been developed. Geometric MDS allows f...

Multi-criteria decision-making (MCDM) methods aim at dealing with certain limitations of human information processing. However, cognitive biases, which are discrepancies of human behavior from the behavior of perfectly rational agents, might persist even when MCDM methods are used. In this article, we focus on two among the most common biases—frami...

The paper deals with the multidimensional scaling (MDS) that depends on the class of nonlinear projection methods for a visual representation of multidimensional data. The performance of a new MDS-type method for multidimensional data dimensionality reduction and visualization (Geometric MDS) has been investigated visually using GeoGebra. Dynamic g...

This book is composed of a selection of articles from The 2021 World Conference on Information Systems and Technologies (WorldCIST'21), held online between 30 and 31 of March and 1 and 2 of April 2021 at Hangra de Heroismo, Terceira Island, Azores, Portugal. WorldCIST is a global forum for researchers and practitioners to present and discuss recent...

This book is composed of a selection of articles from The 2021 World Conference on Information Systems and Technologies (WorldCIST'21), held online between 30 and 31 of March and 1 and 2 of April 2021 at Hangra de Heroismo, Terceira Island, Azores, Portugal. WorldCIST is a global forum for researchers and practitioners to present and discuss recent...

This book is composed of a selection of articles from The 2021 World Conference on Information Systems and Technologies (WorldCIST'21), held online between 30 and 31 of March and 1 and 2 of April 2021 at Hangra de Heroismo, Terceira Island, Azores, Portugal. WorldCIST is a global forum for researchers and practitioners to present and discuss recent...

This book is composed of a selection of articles from The 2021 World Conference on Information Systems and Technologies (WorldCIST'21), held online between 30 and 31 of March and 1 and 2 of April 2021 at Hangra de Heroismo, Terceira Island, Azores, Portugal. WorldCIST is a global forum for researchers and practitioners to present and discuss recent...

Multidimensional scaling (MDS) provides a possibility to present the multidimensional data visually. It is a very popular method of this class. MDS minimizes some stress functions. In this paper, the stress function and multidimensional scaling, in general, have been considered from the geometric point of view. The so-called Geometric MDS has been...

Personal interests constitute the emphasis of client-centered, personalized marketing, which leads to personalized client fulfillment. Current shoppers are interested in more than simply buying products and services; shoppers are also interested in the surroundings of the shopping site. Everywhere in the world, an analysis of marketing value, with...

During the last years, marine traffic dramatically increases. Marine traffic safety highly depends on the mariner’s decisions and particular situations. The watch officer must continuously observe the marine traffic for anomalies because the anomaly detection is crucial to predict dangerous situations and to make a decision in time for safe marine...

The implementation of advertising for green housing usually involves consideration of individual differences among potential buyers, their desires for residential unit features as well as location impacts on a selected property. Much more rarely, there is consideration of the arousal and valence, affective behavior, emotional, and physiological sta...

Multidimensional scaling (MDS) is one of the most popular methods for a visual representation of multidimensional data. A novel geometric interpretation of the stress function and multidimensional scaling in general (Geometric MDS) has been proposed. Following this interpretation, the step size and direction forward the minimum of the stress functi...

This book contains 16 chapters by researchers working in various fields of data science. They focus on theory and applications in language technologies, optimization, computational thinking, intelligent decision support systems, decomposition of signals, model-driven development methodologies, interoperability of enterprise applications, anomaly de...

The research described in this article integrated objective and subjective human analyses of the built environment. These were conducted from two perspectives: that of an individual and that of the built environment. The development of the research design over the course of this study involved 11 phases. A research design using an integrated method...

During the last 10–20 years, a great deal of new ideas have been proposed to improve the accuracy of speech emotion recognition: e.g., effective feature sets, complex classification schemes, and multi-modal data acquisition. Nevertheless, speech emotion recognition is still the task in limited success. Considering the nonlinear and fluctuating natu...

Konferencija „Lietuvos magistrantų informatikos ir IT tyrimai“ skirta pristatyti magistrų baigiamųjų darbų tyrimus informatikos ir IT srityse. Šio renginio tikslas – pakelti magistrantų įgūdžius, supažindinti su kitų magistrantų atliekamais tyrimais, paskatinti domėtis moksline veikla. Konferencijoje savo pranešimus skaitys magistrantai iš Kauno te...

Multiple-criteria decision-making (MCDM) typically assumes that crowds make completely rational decisions. In MCDM, a crowd as a whole, or its individual members, generally make decisions free from any influence of valence, arousal, emotional state or environment. In contrast, various theories dealing with crowd psychology (Gustave Le Bon, Freudian...

Visualization is a part of data science, and essential to enable sophisticated analysis of data. The visualization ensures the human participation in most decisions when analyzing data. In this paper, we review methods and software for visualization of multidimensional data. The emphasis is put on the web-based DAMIS solution for data analysis, all...

The most topical challenges in data science are highlighted. The activities of Vilnius University Institute of Data Science and Digital Technologies are introduced. The institute pretends to solve at least a part of problems arising in this field, first of all, cognitive computing, blockchain technology, development of cyber-social systems and big...

Implementing energy-efficient solutions in a built environment is important for reaching international energy reduction targets. For advanced energy efficiency-related solutions, computer-based decision support systems are proposed and rapidly used in a variety of spheres relevant to a built environment. Present research proposes a novel artificial...

Accurate methods of rapid medical diagnostics would obtain recognition among clinicians. In this paper, we present a ROC (receiver operating characteristic) analysis based approach to investigate intrinsic fluorescence spectra of medical samples. The approach provides researchers with capabilities for both spectroscopic feature selection and classi...

Many diseases can be early detected from eye fundus images by several different features. One of the features is the artery and vein ratio. Width measurement is made on the main vessels. The aim of this automatization process is to create a fully automated method for eye fundus analysis. The fully automated system consists of blood vessel tree extr...

Radiologists need to find a position of a slice of one computed tomography (CT) scan in another scan. The image registration is a technique used to transform several images into one coordinate system and to compare them. Such transversal plane images obtained by CT scans are considered, where ribs are visible, but it does not lessen the significanc...

In this paper, a method for analyzing transversal plane images obtained by computer tomography (CT) scans is presented. A mathematical model that describes the ribs-bounded contour was created and the problem of approximation is solved by finding out the optimal parameters of the model in the least-squares sense. The paper discloses the problems th...

The conventional technologies and methods are not able to store and analyse recent data that come from different sources: various devices, sensors, networks, transactional applications, the web, and social media. Due to a complexity of data, data mining methods should be implemented using the capabilities of the Cloud technologies. In this paper, a...

The method for analysing transversal plane images from computer tomography scans is considered in the paper. This method allows not only approximating ribs-bounded contour but also evaluating patient rotation around the vertical axis during a scan. In this method, a mathematical model describing the ribs-bounded contour was created and the problem...

The prostate cancer is the second most frequent tumor amongst men. Statistics shows that biopsy reveals only 70-80% clinical cancer cases. Multiparametric magnetic resonance imaging (MRI) technique comes to play and is used to help to determine the location to perform a biopsy. With the aim to automating the biopsy localization, prostate segmentati...

In this paper, a Cloud computing approach for intelligent visualization of multidimensional data is proposed. Intelligent visualization enables to create visualization models based on the best practices and experience. A new Cloud computing-based data mining system DAMIS is introduced for the intelligent data analysis including data visualization m...

In this paper a method for analyzing transversal plane images from computer tomography scans is presented. A mathematical model that describes the ribs-bounded contour was created and the problem of approximation is solved by finding out the optimal parameters of the model in the least-squares sense. Such model would be useful in registration of im...

Nowadays business information systems are thought of as decision-oriented systems supported by different types of subsystems. Multidimensional data visualization is an essential part of such systems. As datasets tend to be increasingly large, more effective ways are required to display, analyze and interpret information they contain. Most of the cl...

The estimation of intrinsic dimensionality of high-dimensional data still remains a challenging issue. Various approaches to interpret and estimate the intrinsic dimensionality are developed. Referring to the following two classifications of estimators of the intrinsic dimensionality local/global estimators and projection techniques/geometric appro...

A secure and high-quality operation of power grids requires frequency to be managed to keep it stable around a reference value. The deviation of the frequency from this reference value is caused by the imbalance between the active power produced and consumed. In the Smart Grid paradigm, the balance can be achieved by adjusting the demand to the pro...

One of the problems in the analysis of the set of images of a moving object is to evaluate the degree of freedom of motion and the angle of rotation. Here the intrinsic dimensionality of multidimensional data, characterizing the set of images, can be used. Usually, the image may be represented by a high-dimensional point whose dimensionality depend...

The aim of this paper is to create a new recommendation method that would evaluate the peculiarities of user groups, and to examine experimentally the efficiency of user clustering in order to improve the recommendations. To achieve this goal, we have analysed recommendation systems (RS), their components, operating principles and data, used for ac...

The analysis of medical streaming data is quite difficult when the problem is to estimate health-state situations in real time streaming data in accordance with the previously detected and estimated streaming data of various patients. This paper deals with the multivariate time series analysis seeking to compare the current situation (sample) with...

Business information systems nowadays should be thought of first of all as the decision-oriented systems supported by different types of subsystems. Multidimensional data visualization is an essential constituent of such systems, especially in the age of growing amounts of data to be interpreted and analyzed. As managers are faced with a federated...

The paper summarizes the results of research on the modeling and implementation of advanced planning and scheduling (APS) systems done in recent twenty years. It discusses the concept of APS system – how it is thought of today – and highlights the modeling and implementation challenges with which the developers of such systems should cope. Some fro...

Dimensionality reduction is a very important tool in data mining. An intrinsic dimensionality of a data set is a key parameter in many dimensionality reduction algorithms. When the intrinsic dimensionality of a data set is known, it is possible to reduce the dimensionality of the data without losing much information. To this end, it is reasonable t...

This chapter is intended for applications of multidimensional data visualization. Some application examples and interpretations of the results are presented. These applications reveal the possibilities and advantages of the visual analysis. The applications can be grouped as follows: in social sciences, in medicine and pharmacology, and visual anal...

In this chapter, we consider one of themost popular approaches of multidimensional data visualization, known as multidimensional scaling (MDS) [14, 31, 127, 139, 150, 191, 202]. The essential part of this technique is optimization of a function possessing many optimization adverse properties [231]. By means of MDS, a set of objects can be represent...

In this chapter, an analytical review of methods for multidimensional data visualization is presented. The methods based on direct visualization and projections are described. Some quantitative criteria of the visualization quality are also introduced.

Frequent sequence mining is one of the main challenges in data mining and especially in large databases, which consist of millions of records. There is a number of different applications where frequent sequence mining is very important: medicine, finance, internet behavioural data, marketing data, etc. Exact frequent sequence mining methods make mu...

It is often desirable to visualize a data set, the items of which are described by more than three features. Therefore, we have multidimensional data, and our goal is to make some visual insight into the data set analyzed. For human perception, the data must be represented in a low-dimensional space, usually of two or three dimensions. The goal of...

The combination and integrated use of data visualization methods of a different nature are under a rapid development. The combination of different methods can be applied to make a data analysis, while minimizing the shortcomings of individual methods. This chapter is devoted to visualization methods based on an artificial neural network. The fundam...

Straipsnis skiriamas rekomendacinių sistemų algoritmų veikimo konkrečioje elektroninės parduotuvės duomenų bazėje analizei. Analizės tikslas – pagal pasirinktus įverčius rasti rekomendacinių sistemų algoritmus, efektyviausiai veikiančius turimoje duomenų bazėje. Šiame straipsnyje palyginti nemokamos rekomendacinių sistemų programinės įrangos paketa...

The analysis of the online customer shopping behavior is an important task nowadays, which allows maximizing the efficiency of advertising campaigns and increasing the return of investment for advertisers. The analysis results of online customer shopping behavior are usually reviewed and understood by a non-technical person; therefore the results m...

Retinal (eye fundus) images are widely used for diagnostic purposes by ophthalmologists. The normal features of eye fundus images include the optic nerve disc, fovea and blood vessels. Algorithms for identifying blood vessels in the eye fundus image generally fall into two classes: extraction of vessel information and segmentation of vessel pixels....

The paper proposes a novel predictive–reactive planning and scheduling framework in which both approaches are combined in order to complement each other in a reasonably balanced way. It proposes neither any original scheduling algorithms nor techniques. It also not aims to invent some new mechanisms or to propose some cardinally new ideas. The aim...

While analyzing multidimensional data, we often have to reduce their dimensionality so that to preserve as much information on the analyzed data set as possible. To this end, it is reasonable to find out the intrinsic dimensionality of the data. In this paper, two techniques for the intrinsic dimensionality are analyzed and compared, i.e., the maxi...

In this paper, we present an approach of the Web application (as a service) for data mining oriented to the multidimensional data visualization. The stress is put on visualization methods as a tool for the visual presentation of large-scale multidimensional data sets. The proposed implementation includes five visualization methods: MDS SMACOF algor...

This article describes the analysis of emotional state and work productivity using a Web-based Biometric Computer Mouse Advisory System to Analyze a User's Emotions and Work Productivity (Advisory system hereafter) developed by this paper's authors. The Advisory system determines the level of emotional state and work productivity integrally by empl...

In this paper, we present an approach of the web application (as a service) for data mining oriented to the multidimensional data visualization. This paper focuses on visualization methods as a tool for the visual presentation of large-scale multidimensional data sets. The proposed implementation of such a web application obtains a multidimensional...

The experiences of undergoing economic crises attest that the loss of employment prompts an outbreak of mental illnesses and suicides, increases the numbers of heart attacks and strokes and negatively affects other illnesses suffered by individuals under stress. Negative stress can devastate a person, cause depression, lower productivity on the job...