Aelita Skaržauskienė, M. Maciuliene, Ornela Ramasauskaite
The prevalence of so-called “fake news” is a relatively recent social phenomenon that is linked to disinformation, misinformation and other forms of networked manipulation facilitated by the rise of the Internet and online social media. The spread of misinformation is among the most pressing challenges of our time. Sources from which disinformation originates are constantly changing and present an enormous challenge for real-time detection algorithms and more targeted science based socio-technical interventions. The primary aim of this paper is to illuminate the practices and interpretations, focusing on three perspectives: general attitudes to fake news, perceived interaction with disinformation and opinion on counteraction with respect to fake news. The innovative character of the research is achieved by the focus on community solutions to combat disinformation and the collaboration between media users, media organizations, scientists, communication managers, journalists and other important actors in the media ecosystem. Based on insights from interviews with communication field experts, the paper sheds light on the efforts of Lithuanian society to confront the problem of fake news in digital media environment. Lithuania is also an interesting case study for fake news due to its status as a former Soviet state now in the EU. Our research indicates that not all media users are prepared and/or have the necessary competencies to combat fake news, so that citizen engagement might actually negatively influence the quality of the counteraction process. Indeed, proactive citizens’ organizations and NGOs could be an important catalyst fostering collaboration between stakeholders. The responsibility of governments could be to create the structures, methodologies and supporting educational activities to involve the stakeholders in collaborating activities combating disinformation.
{"title":"The Digital Media in Lithuania: Combating Disinformation and Fake News","authors":"Aelita Skaržauskienė, M. Maciuliene, Ornela Ramasauskaite","doi":"10.18267/j.aip.134","DOIUrl":"https://doi.org/10.18267/j.aip.134","url":null,"abstract":"The prevalence of so-called “fake news” is a relatively recent social phenomenon that is linked to disinformation, misinformation and other forms of networked manipulation facilitated by the rise of the Internet and online social media. The spread of misinformation is among the most pressing challenges of our time. Sources from which disinformation originates are constantly changing and present an enormous challenge for real-time detection algorithms and more targeted science based socio-technical interventions. The primary aim of this paper is to illuminate the practices and interpretations, focusing on three perspectives: general attitudes to fake news, perceived interaction with disinformation and opinion on counteraction with respect to fake news. The innovative character of the research is achieved by the focus on community solutions to combat disinformation and the collaboration between media users, media organizations, scientists, communication managers, journalists and other important actors in the media ecosystem. Based on insights from interviews with communication field experts, the paper sheds light on the efforts of Lithuanian society to confront the problem of fake news in digital media environment. Lithuania is also an interesting case study for fake news due to its status as a former Soviet state now in the EU. Our research indicates that not all media users are prepared and/or have the necessary competencies to combat fake news, so that citizen engagement might actually negatively influence the quality of the counteraction process. Indeed, proactive citizens’ organizations and NGOs could be an important catalyst fostering collaboration between stakeholders. The responsibility of governments could be to create the structures, methodologies and supporting educational activities to involve the stakeholders in collaborating activities combating disinformation.","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43846426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scientific and technological developments in informatics enable intensive transformation of data into valuable information. Enriched with context, information may be turned into knowledge, allowing organizations to optimize their processes and profile themselves as learning knowledge organizations. Several classifications of knowledge and knowledge management are available in scientific literature and research publications. In this paper the implementation and application of information and communication technology in knowledge management is being assessed from the perspective of synchrony and mutual interaction among collaborating parties. Following the PRISMA scheme, a systematic review procedure using Scopus and Web of Science databases was conducted. Obtained manuscripts underwent manual content analysis. The outcome of this analysis represents the classification of widespread ICTs into diverse categories based on extensive literature research. It specifies an original type of classification by connecting intertwined synchronicity and interaction as the main classification criteria, and it provides examples of commonly used ICTs in business practice. The introduced classification aims to deepen the comprehension of ICTs, which may lead to improved efficiency and/or eligibility of technological implementations and applications of knowledge management based on the undeniably enormous benefits of the use of ICTs in processing of business operations.
信息学的科学和技术发展使数据能够密集地转化为有价值的信息。通过丰富上下文，信息可以转化为知识，允许组织优化其过程并将自己描述为学习型知识组织。在科学文献和研究出版物中可以找到知识和知识管理的几种分类。本文从合作方的同步性和相互交互性的角度对信息通信技术在知识管理中的实施和应用进行了评价。按照PRISMA方案，使用Scopus和Web of Science数据库进行系统评审程序。获得的手稿进行了手工内容分析。这一分析的结果表明，基于广泛的文献研究，将广泛使用的信息通信技术分为不同的类别。它通过将相互交织的同步性和交互性连接起来作为主要分类标准，指定了一种原始类型的分类，并提供了在商业实践中常用的信息通信技术的示例。引入的分类旨在加深对信息通信技术的理解，这可能会提高技术实施和知识管理应用的效率和/或资格，因为在处理业务操作中使用信息通信技术带来了不可否认的巨大好处。
{"title":"Knowledge Management-Enabling Technologies: A Supplementary Classification","authors":"Monika Dávideková, M. Greguš, M. Zanker, V. Bureš","doi":"10.18267/j.aip.130","DOIUrl":"https://doi.org/10.18267/j.aip.130","url":null,"abstract":"Scientific and technological developments in informatics enable intensive transformation of data into valuable information. Enriched with context, information may be turned into knowledge, allowing organizations to optimize their processes and profile themselves as learning knowledge organizations. Several classifications of knowledge and knowledge management are available in scientific literature and research publications. In this paper the implementation and application of information and communication technology in knowledge management is being assessed from the perspective of synchrony and mutual interaction among collaborating parties. Following the PRISMA scheme, a systematic review procedure using Scopus and Web of Science databases was conducted. Obtained manuscripts underwent manual content analysis. The outcome of this analysis represents the classification of widespread ICTs into diverse categories based on extensive literature research. It specifies an original type of classification by connecting intertwined synchronicity and interaction as the main classification criteria, and it provides examples of commonly used ICTs in business practice. The introduced classification aims to deepen the comprehension of ICTs, which may lead to improved efficiency and/or eligibility of technological implementations and applications of knowledge management based on the undeniably enormous benefits of the use of ICTs in processing of business operations.","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41617038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper deals with the prediction of company bankruptcies and defines how this undesirable state can be prevented. Currently, these methods include modern approaches from the area of data mining that can help companies in many ways. In a practical application of data mining methods for predicting the future state of a company, financial indicators of Polish companies were used. In the analyses, we used algorithms suitable for bankruptcy prediction – decision trees that provide a simple interpretation of results. In some experiments, we also used attribute selection methods, LASSO, or the PCA method. The workflow is governed by the CRISP-DM methodology, which describes the important steps needed for different analytical tasks. Part of the article is an analysis of the current state, which presents solutions to this problem suggested by other authors. After evaluating all models, we concluded that the C5.0 algorithm is capable of predicting a company’s bankruptcy or non-bankruptcy with 97.07 % accuracy, without the use of attribute selection methods.
{"title":"Data Mining from the Banking Sector´s Data","authors":"Anna Biceková, Ludmila Pusztová","doi":"10.18267/j.aip.123","DOIUrl":"https://doi.org/10.18267/j.aip.123","url":null,"abstract":"This paper deals with the prediction of company bankruptcies and defines how this undesirable state can be prevented. Currently, these methods include modern approaches from the area of data mining that can help companies in many ways. In a practical application of data mining methods for predicting the future state of a company, financial indicators of Polish companies were used. In the analyses, we used algorithms suitable for bankruptcy prediction – decision trees that provide a simple interpretation of results. In some experiments, we also used attribute selection methods, LASSO, or the PCA method. The workflow is governed by the CRISP-DM methodology, which describes the important steps needed for different analytical tasks. Part of the article is an analysis of the current state, which presents solutions to this problem suggested by other authors. After evaluating all models, we concluded that the C5.0 algorithm is capable of predicting a company’s bankruptcy or non-bankruptcy with 97.07 % accuracy, without the use of attribute selection methods.","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"67745064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of the article is to detect and review existing topic modelling methods of Latent Dirichlet Allocation and their modifications usable in Voice of Customer analysis. Voice of Customer is expressed mainly through textual comments which often focus on the evaluation of products or services the customer consumes. The most studied data source are customer reviews which contain next to the textual comments also ratings in form of scales. The aim of the topic models is to mine the topics and their aspects the customers are evaluating in their reviews and assign to them a particular sentiment or emotion. The author completed a systematic literature review of peer-reviewed published journal articles indexed in leading databases of Scopus and Web of Science and concerning the current use of Latent Dirichlet Allocation model variants in Voice of Customer textual analysis for performing the tasks of aspect detection, emotion detection, personality detection and sentiment assignation. In total, 38 modifications of the LDA model were identified with the reference to their first application in the research of text analytics. The review is intended for researchers in customer analytics the field of sentiment or emotion detection, and moreover as results from the review, for studies in personality recognition based on the textual data. The review offers a basic overview and comparison of LDA modifications which can be considered as a knowledge baseline for selection in a specific application. The scope of the literature examination is limited to the period of years 2003–2018 with the application relevant to the analysis of Voice of Customer subjective textual data only which is closely connected to the area of marketing or customer relationship management.
本文的目的是检测和回顾现有的潜在狄利克雷分配的主题建模方法及其修改可用于客户之声分析。顾客的声音主要是通过文本评论来表达的，这些评论往往集中在对顾客消费的产品或服务的评价上。研究最多的数据来源是客户评论，它包含在文本评论旁边也以尺度的形式评级。主题模型的目的是挖掘客户在评论中评估的主题及其方面，并为它们分配特定的情绪或情感。作者完成了一项系统的文献综述，检索了Scopus和Web of Science等领先数据库中同行评审的已发表期刊文章，并研究了目前在Customer Voice文本分析中使用Latent Dirichlet Allocation模型变体执行方面检测、情感检测、个性检测和情感分配任务的情况。总共有38个LDA模型的修改，参考了它们在文本分析研究中的首次应用。这篇综述的目的是为客户分析领域的研究人员提供情感或情感检测，并且作为综述的结果，用于基于文本数据的人格识别研究。该综述提供了LDA修改的基本概述和比较，可被视为在特定应用中选择的知识基线。文献检查的范围仅限于2003-2018年期间，仅与客户主观文本数据分析相关的应用程序与营销或客户关系管理领域密切相关。
{"title":"Review of Latent Dirichlet Allocation Methods Usable in Voice of Customer Analysis","authors":"Lucie Sperková","doi":"10.18267/j.aip.120","DOIUrl":"https://doi.org/10.18267/j.aip.120","url":null,"abstract":"The aim of the article is to detect and review existing topic modelling methods of Latent Dirichlet Allocation and their modifications usable in Voice of Customer analysis. Voice of Customer is expressed mainly through textual comments which often focus on the evaluation of products or services the customer consumes. The most studied data source are customer reviews which contain next to the textual comments also ratings in form of scales. The aim of the topic models is to mine the topics and their aspects the customers are evaluating in their reviews and assign to them a particular sentiment or emotion. The author completed a systematic literature review of peer-reviewed published journal articles indexed in leading databases of Scopus and Web of Science and concerning the current use of Latent Dirichlet Allocation model variants in Voice of Customer textual analysis for performing the tasks of aspect detection, emotion detection, personality detection and sentiment assignation. In total, 38 modifications of the LDA model were identified with the reference to their first application in the research of text analytics. The review is intended for researchers in customer analytics the field of sentiment or emotion detection, and moreover as results from the review, for studies in personality recognition based on the textual data. The review offers a basic overview and comparison of LDA modifications which can be considered as a knowledge baseline for selection in a specific application. The scope of the literature examination is limited to the period of years 2003–2018 with the application relevant to the analysis of Voice of Customer subjective textual data only which is closely connected to the area of marketing or customer relationship management.","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41722959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. A. Orunsolu, O. Afolabi, A. Sodiya, A. Akinwale
Security tips are now used as a method of priming online users from falling prey for fraudulent scams. These security tips usually come as email, SMS or online posts where they can be easily accessed by the users. In this work, phishing attacks are simulated with varying cues that are available in such fraudulent email messages, SMS and web pages were used to investigate the effectiveness of the security tips used by Nigerian banks to prime their customers of online threats. A total of 427 respondents, purposively selected from three tertiary institutions in Ogun State, participated in the study. Each respondent was asked to identify five messages with varying phishing cues to evaluate their understanding of the security tips messages. The results which were computed at 95% Confidence Interval, indicated that 58.91% failed on the first attribute, 58.59% failed on the second attribute while 58.73% failed on the third attribute. 74.24% of the participant could not correctly identify a fake email message (fourth attribute) while 76.71% could not correctly identify a phished bank verification number update message (fifth attribute). Using the Mann Whitney Test, the result further showed that overall, those who failed the test are significantly more than those who passed. Moreover, a regression model is proposed to evaluate the influence of the socio demographic factors used in the study. This result indicated that gender, academic qualification and user's computer knowledge significantly influences their ability to recognize phished messages.
{"title":"A Users' Awareness Study and Influence of Socio-Demography Perception of Anti-Phishing Security Tips","authors":"A. A. Orunsolu, O. Afolabi, A. Sodiya, A. Akinwale","doi":"10.18267/j.aip.119","DOIUrl":"https://doi.org/10.18267/j.aip.119","url":null,"abstract":"Security tips are now used as a method of priming online users from falling prey for fraudulent scams. These security tips usually come as email, SMS or online posts where they can be easily accessed by the users. In this work, phishing attacks are simulated with varying cues that are available in such fraudulent email messages, SMS and web pages were used to investigate the effectiveness of the security tips used by Nigerian banks to prime their customers of online threats. A total of 427 respondents, purposively selected from three tertiary institutions in Ogun State, participated in the study. Each respondent was asked to identify five messages with varying phishing cues to evaluate their understanding of the security tips messages. The results which were computed at 95% Confidence Interval, indicated that 58.91% failed on the first attribute, 58.59% failed on the second attribute while 58.73% failed on the third attribute. 74.24% of the participant could not correctly identify a fake email message (fourth attribute) while 76.71% could not correctly identify a phished bank verification number update message (fifth attribute). Using the Mann Whitney Test, the result further showed that overall, those who failed the test are significantly more than those who passed. Moreover, a regression model is proposed to evaluate the influence of the socio demographic factors used in the study. This result indicated that gender, academic qualification and user's computer knowledge significantly influences their ability to recognize phished messages.","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45333056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Social media networks are tools that recruiters can utilize during a recruitment process. Most importantly, social media networks can be used in conjunction with applications capable of downloading information about their potential candidates. The aim of this article is to present a creation process of a model that could be helpful in recruiting area. A crucial part of this model is application software that downloads user’s data, particularly from Facebook profiles. This model should propose appropriate analytical methods for data processing. The output of this article is employee recruitment model that can be used as a guide to utilize the potential of social media networks by HR professionals. Test run of this model on our population sample showed prediction accuracy of 68 % to 84 %.
{"title":"Analyzing Social Media Data for Recruiting Purposes","authors":"L. Bohmova, David Chudán","doi":"10.18267/j.aip.111","DOIUrl":"https://doi.org/10.18267/j.aip.111","url":null,"abstract":"Social media networks are tools that recruiters can utilize during a recruitment process. Most importantly, social media networks can be used in conjunction with applications capable of downloading information about their potential candidates. The aim of this article is to present a creation process of a model that could be helpful in recruiting area. A crucial part of this model is application software that downloads user’s data, particularly from Facebook profiles. This model should propose appropriate analytical methods for data processing. The output of this article is employee recruitment model that can be used as a guide to utilize the potential of social media networks by HR professionals. Test run of this model on our population sample showed prediction accuracy of 68 % to 84 %.","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44145665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of the article is to give a survey of research fields related to test and manage applications from the cloud, i.e. cloud-based testing, so that it can facilitate security requirements associated with the testing. This article has two main aims. The first one is the survey of published results attained by the synergy of these research fields – cloud-based testing, testing strategies and types of tests, and related architectures, which is followed by the classification of testing tools based on their testing strategies. The second part is focused on security testing of Fire and Rescue Service portals in the Czech Republic and identification of vulnerabilities in these portals. The results suggested that it is more appropriate to manage only one unified portal than a lot of portals on the regional level, also due to the economies of scale. Finally, the most suitable tool for cloud-based security testing was recommended based on these results and a typical cloud-based testing methodology was described.
{"title":"Classification and Evaluation of Cloud-Based Testing Tools: The Case Study of Web Applications' Security Testing","authors":"Martin Lnenicka, J. Čapek","doi":"10.18267/j.aip.113","DOIUrl":"https://doi.org/10.18267/j.aip.113","url":null,"abstract":"The purpose of the article is to give a survey of research fields related to test and manage applications from the cloud, i.e. cloud-based testing, so that it can facilitate security requirements associated with the testing. This article has two main aims. The first one is the survey of published results attained by the synergy of these research fields – cloud-based testing, testing strategies and types of tests, and related architectures, which is followed by the classification of testing tools based on their testing strategies. The second part is focused on security testing of Fire and Rescue Service portals in the Czech Republic and identification of vulnerabilities in these portals. The results suggested that it is more appropriate to manage only one unified portal than a lot of portals on the regional level, also due to the economies of scale. Finally, the most suitable tool for cloud-based security testing was recommended based on these results and a typical cloud-based testing methodology was described.","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47151677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Obecna uměla inteligence usiluje o vytvořeni umělých systemů schopných řesit mnoho různých, a to i během vývoje nepředvidaných, uloh, což takove systemy cini svou inteligenci srovnatelne s lidmi. To vsak vyžaduje existenci vhodných metod vyhodnocujicich, zda a nakolik jsou uměle systemy inteligentni. Tento přehledový clanek hleda pravě takove evaluacni metody. Provadi proto rozsahlou resersi literatury pokrývajici jak filosoficke a kognitivni předpoklady inteligence, tak i formalni definice a prakticke testy vychazejici z algoritmicke teorie informace. Na zakladě porovnani představených metod clanek odhaluje dvě rozdilne skupiny přistupů založene na principialně odlisných předpokladech. Zatimco starsi přistupy, jako např. Turingův test, jsou založeny na předpokladu, že uspěch v komplexni cinnosti je postacujici pro přiznani inteligence, nove přistupy, jako např. test algoritmickeho IQ, kromě toho vyžaduji i důkladne ověřeni uspěsnosti v jednoduchých cinnostech. V důsledku tohoto zjistěni clanek dochazi k zavěru, že test algoritmickeho IQ založený na definici univerzalni inteligence je v soucasne době nejlepsim kandidatem na vhodný prakticky proveditelný test obecne inteligence umělých systemů. Ackoliv i tento test ma několik znamých limitů.
{"title":"Přehled přístupů k vyhodnocování inteligence umělých systémů","authors":"Ondrej Vadinský","doi":"10.18267/j.aip.115","DOIUrl":"https://doi.org/10.18267/j.aip.115","url":null,"abstract":"Obecna uměla inteligence usiluje o vytvořeni umělých systemů schopných řesit mnoho různých, a to i během vývoje nepředvidaných, uloh, což takove systemy cini svou inteligenci srovnatelne s lidmi. To vsak vyžaduje existenci vhodných metod vyhodnocujicich, zda a nakolik jsou uměle systemy inteligentni. Tento přehledový clanek hleda pravě takove evaluacni metody. Provadi proto rozsahlou resersi literatury pokrývajici jak filosoficke a kognitivni předpoklady inteligence, tak i formalni definice a prakticke testy vychazejici z algoritmicke teorie informace. Na zakladě porovnani představených metod clanek odhaluje dvě rozdilne skupiny přistupů založene na principialně odlisných předpokladech. Zatimco starsi přistupy, jako např. Turingův test, jsou založeny na předpokladu, že uspěch v komplexni cinnosti je postacujici pro přiznani inteligence, nove přistupy, jako např. test algoritmickeho IQ, kromě toho vyžaduji i důkladne ověřeni uspěsnosti v jednoduchých cinnostech. V důsledku tohoto zjistěni clanek dochazi k zavěru, že test algoritmickeho IQ založený na definici univerzalni inteligence je v soucasne době nejlepsim kandidatem na vhodný prakticky proveditelný test obecne inteligence umělých systemů. Ackoliv i tento test ma několik znamých limitů.","PeriodicalId":36592,"journal":{"name":"Acta Informatica Pragensia","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43679999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Chudán, V. Svátek, Jaroslav Kuchař, Stanislav Vojíř
Metody dolovani z dat jsou aplikovany ve stale větsi miře, a to i v domenach, ktere tradicně nemaji tak silnou podporu analytických nastrojů a kde převlada rucni prace analytika. Použiti těchto metod v oblasti fiskalnich dat umožni jejich hlubsi analýzu a může přinest nova zjistěni. Nasazeni pokrocilých metod dolovani z dat je jednou z casti projektu OpenBudgets.eu, který se zaměřuje na transparentnost a odpovědnost v oblasti nakladani s veřejnými prostředky. Tento přehledový clanek shrnuje některe zkusenosti autorů z tohoto projektu ziskane při vývoji, implementaci a aplikaci vybraných metod dolovani z fiskalnich dat. Jedna se zejmena o metody detekce anomalii a dolovani asociacnich pravidel. Tyto metody jsou integrovany do centralni platformy projektu, ktera je k dispozici pokrocilým i běžným uživatelům v připadě zajmu o analýzu fiskalnich dat. Pilotni analýzy ukazaly, že problemem dataminingove analýzy v teto domeně je velký objem nachazených pravidel a různorodý původ jejich vzniku.
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