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  1. Book ; Online: Towards replicated algorithms

    Fister Jr., Iztok / Fister, Iztok

    2023  

    Abstract: The main deficiency of the algorithms running on digital computers nowadays is their inability to change themselves during the execution. In line with this, the paper introduces the so-called replicated algorithms, inspired by the concept of developing a ...

    Abstract The main deficiency of the algorithms running on digital computers nowadays is their inability to change themselves during the execution. In line with this, the paper introduces the so-called replicated algorithms, inspired by the concept of developing a human brain. Similar to the human brain, where the process of thinking is strongly parallel, replicated algorithms, incorporated into a population, are also capable of replicating themselves and solving problems in parallel. They operate as a model for mapping the known input to a known output. In our preliminary study, these algorithms are built as sequences of arithmetic operators, applied for calculating arithmetic expressions, while their behavior showed that they can operate in the condition of open-ended evolution.
    Keywords Computer Science - Neural and Evolutionary Computing
    Publishing date 2023-03-31
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Book ; Online: Profiling the carbon footprint of performance bugs

    Fister Jr., Iztok / Fister, Dušan / Podgorelec, Vili / Fister, Iztok

    2024  

    Abstract: Much debate nowadays is devoted to the impacts of modern information and communication technology on global carbon emissions. Green information and communication technology is a paradigm creating a sustainable and environmentally friendly computing field ...

    Abstract Much debate nowadays is devoted to the impacts of modern information and communication technology on global carbon emissions. Green information and communication technology is a paradigm creating a sustainable and environmentally friendly computing field that tries to minimize the adverse effects on the environment. Green information and communication technology are under constant development nowadays. Thus, in this paper, we undertake the problem of performance bugs that, until recently, have never been studied so profoundly. We assume that inappropriate software implementations can have a crucial influence on global carbon emissions. Here, we classify those performance bugs and develop inappropriate implementations of four programs written in C++. To mitigate these simulated performance bugs, measuring software and hardware methods that can estimate the increased carbon footprint properly were proposed.
    Keywords Computer Science - Software Engineering
    Subject code 303
    Publishing date 2024-01-03
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Book ; Online: Numerical Association Rule Mining

    Kaushik, Minakshi / Sharma, Rahul / Fister Jr., Iztok / Draheim, Dirk

    A Systematic Literature Review

    2023  

    Abstract: Numerical association rule mining is a widely used variant of the association rule mining technique, and it has been extensively used in discovering patterns and relationships in numerical data. Initially, researchers and scientists integrated numerical ... ...

    Abstract Numerical association rule mining is a widely used variant of the association rule mining technique, and it has been extensively used in discovering patterns and relationships in numerical data. Initially, researchers and scientists integrated numerical attributes in association rule mining using various discretization approaches; however, over time, a plethora of alternative methods have emerged in this field. Unfortunately, the increase of alternative methods has resulted into a significant knowledge gap in understanding diverse techniques employed in numerical association rule mining -- this paper attempts to bridge this knowledge gap by conducting a comprehensive systematic literature review. We provide an in-depth study of diverse methods, algorithms, metrics, and datasets derived from 1,140 scholarly articles published from the inception of numerical association rule mining in the year 1996 to 2022. In compliance with the inclusion, exclusion, and quality evaluation criteria, 68 papers were chosen to be extensively evaluated. To the best of our knowledge, this systematic literature review is the first of its kind to provide an exhaustive analysis of the current literature and previous surveys on numerical association rule mining. The paper discusses important research issues, the current status, and future possibilities of numerical association rule mining. On the basis of this systematic review, the article also presents a novel discretization measure that contributes by providing a partitioning of numerical data that meets well human perception of partitions.
    Keywords Computer Science - Machine Learning ; Computer Science - Databases
    Subject code 006
    Publishing date 2023-07-02
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Book ; Online: Association rules over time

    Fister Jr., Iztok / Fister, Iztok

    2020  

    Abstract: Decisions made nowadays by Artificial Intelligence powered systems are usually hard for users to understand. One of the more important issues faced by developers is exposed as how to create more explainable Machine Learning models. In line with this, ... ...

    Abstract Decisions made nowadays by Artificial Intelligence powered systems are usually hard for users to understand. One of the more important issues faced by developers is exposed as how to create more explainable Machine Learning models. In line with this, more explainable techniques need to be developed, where visual explanation also plays a more important role. This technique could also be applied successfully for explaining the results of Association Rule Mining.This Chapter focuses on two issues: (1) How to discover the relevant association rules, and (2) How to express relations between more attributes visually. For the solution of the first issue, the proposed method uses Differential Evolution, while Sankey diagrams are adopted to solve the second one. This method was applied to a transaction database containing data generated by an amateur cyclist in past seasons, using a mobile device worn during the realization of training sessions that is divided into four time periods. The results of visualization showed that a trend in improving performance of an athlete can be indicated by changing the attributes appearing in the selected association rules in different time periods.
    Keywords Computer Science - Neural and Evolutionary Computing ; Computer Science - Artificial Intelligence
    Subject code 006
    Publishing date 2020-10-08
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Book ; Online: A brief overview of swarm intelligence-based algorithms for numerical association rule mining

    Fister Jr., Iztok / Fister, Iztok

    2020  

    Abstract: Numerical Association Rule Mining is a popular variant of Association Rule Mining, where numerical attributes are handled without discretization. This means that the algorithms for dealing with this problem can operate directly, not only with categorical, ...

    Abstract Numerical Association Rule Mining is a popular variant of Association Rule Mining, where numerical attributes are handled without discretization. This means that the algorithms for dealing with this problem can operate directly, not only with categorical, but also with numerical attributes. Until recently, a big portion of these algorithms were based on a stochastic nature-inspired population-based paradigm. As a result, evolutionary and swarm intelligence-based algorithms showed big efficiency for dealing with the problem. In line with this, the main mission of this chapter is to make a historical overview of swarm intelligence-based algorithms for Numerical Association Rule Mining, as well as to present the main features of these algorithms for the observed problem. A taxonomy of the algorithms was proposed on the basis of the applied features found in this overview. Challenges, waiting in the future, finish this paper.
    Keywords Computer Science - Neural and Evolutionary Computing
    Subject code 006
    Publishing date 2020-10-29
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Book ; Online: Information cartography in association rule mining

    Fister Jr., Iztok / Fister, Iztok

    2020  

    Abstract: Association Rule Mining is a data mining method for discovering the interesting relations between attributes in a huge transaction database. Typically, algorithms for association rule mining generate a huge number of association rules, from which it is ... ...

    Abstract Association Rule Mining is a data mining method for discovering the interesting relations between attributes in a huge transaction database. Typically, algorithms for association rule mining generate a huge number of association rules, from which it is hard to extract structured knowledge and automatically present this in a form that would be suitable for the user. Recently, an information cartography has been proposed for creating structured summaries of information and visualizing with methodology called "metro maps". This was applied to many problem domains. In the hope of widening its applicability domain, the aim of this study is to develop a method for the automatic creation of metro maps of information obtained by association rule mining. Although the proposed method consists of multiple steps, its core presents metro map construction that is defined in the study as an optimization problem, which is solved using an evolutionary algorithm. Finally, this was applied to four well-known UCI Machine Learning datasets and one sport dataset. Visualizing the resulted metro maps not only justifies the fact this is a suitable tool for presenting structured knowledge hidden in data, but also that they can even tell stories to users.
    Keywords Computer Science - Neural and Evolutionary Computing
    Subject code 006
    Publishing date 2020-02-29
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Book ; Online: A comprehensive review of visualization methods for association rule mining

    Fister Jr., Iztok / Fister, Iztok / Fister, Dušan / Podgorelec, Vili / Salcedo-Sanz, Sancho

    Taxonomy, Challenges, Open problems and Future ideas

    2023  

    Abstract: Association rule mining is intended for searching for the relationships between attributes in transaction databases. The whole process of rule discovery is very complex, and involves pre-processing techniques, a rule mining step, and post-processing, in ... ...

    Abstract Association rule mining is intended for searching for the relationships between attributes in transaction databases. The whole process of rule discovery is very complex, and involves pre-processing techniques, a rule mining step, and post-processing, in which visualization is carried out. Visualization of discovered association rules is an essential step within the whole association rule mining pipeline, to enhance the understanding of users on the results of rule mining. Several association rule mining and visualization methods have been developed during the past decades. This review paper aims to create a literature review, identify the main techniques published in peer-reviewed literature, examine each method's main features, and present the main applications in the field. Defining the future steps of this research area is another goal of this review paper.
    Keywords Computer Science - Databases ; Computer Science - Artificial Intelligence
    Publishing date 2023-02-24
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

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  8. Book ; Online: Adaptation and hybridization in computational intelligence

    Fister Jr., Iztok / Fister, Iztok

    (Adaptation, Learning, and Optimization ; 18)

    2015  

    Abstract: This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background ... ...

    Author's details ed. by Iztok Fister, Iztok Fister Jr
    Series title Adaptation, Learning, and Optimization ; 18
    Abstract This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence -based algorithms.
    Keywords Artificial intelligence ; Engineering
    Language English
    Size Online-Ressource (X, 237 S., Ill.), online resource
    Publisher Springer
    Publishing place Cham
    Document type Book ; Online
    Note Description based upon print version of record
    ISBN 9783319143996 ; 9783319144009 ; 3319143999 ; 3319144006
    DOI 10.1007/978-3-319-14400-9
    Database Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  9. Book ; Online: Adaptation and hybridization in computational intelligence

    Fister Jr., Iztok / Fister, Iztok

    (Adaptation, Learning, and Optimization ; 18)

    2015  

    Abstract: This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background ... ...

    Author's details ed. by Iztok Fister, Iztok Fister Jr
    Series title Adaptation, Learning, and Optimization ; 18
    Abstract This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence -based algorithms.
    Keywords Artificial intelligence ; Engineering
    Language English
    Size Online-Ressource (X, 237 S., Ill.), online resource
    Publisher Springer
    Publishing place Cham
    Document type Book ; Online
    Note Description based upon print version of record
    ISBN 9783319143996 ; 9783319144009 ; 3319143999 ; 3319144006
    DOI 10.1007/978-3-319-14400-9
    Database Former special subject collection: coastal and deep sea fishing

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    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  10. Book ; Online: Discovering associations in COVID-19 related research papers

    Fister Jr., Iztok / Fister, Karin / Fister, Iztok

    2020  

    Abstract: A COVID-19 pandemic has already proven itself to be a global challenge. It proves how vulnerable humanity can be. It has also mobilized researchers from different sciences and different countries in the search for a way to fight this potentially fatal ... ...

    Abstract A COVID-19 pandemic has already proven itself to be a global challenge. It proves how vulnerable humanity can be. It has also mobilized researchers from different sciences and different countries in the search for a way to fight this potentially fatal disease. In line with this, our study analyses the abstracts of papers related to COVID-19 and coronavirus-related-research using association rule text mining in order to find the most interestingness words, on the one hand, and relationships between them on the other. Then, a method, called information cartography, was applied for extracting structured knowledge from a huge amount of association rules. On the basis of these methods, the purpose of our study was to show how researchers have responded in similar epidemic/pandemic situations throughout history.

    Comment: arXiv admin note: text overlap with arXiv:2003.00348
    Keywords Computer Science - Information Retrieval ; Computer Science - Artificial Intelligence ; Computer Science - Social and Information Networks ; covid19
    Subject code 001
    Publishing date 2020-04-06
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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