Wyniki wyszukiwania - BazTech

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The use of chatbots and voicebots by public institutions in the communication process with clients

Noga Tomasz

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2023

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z. 174

69--80

EN

Purpose: The purpose of this publication is to identify the opportunities and threats arising from the use of chatbots and voicebots in Polish public sector institutions. Design/methodology/approach: The theoretical basis presented in this paper is the available literature on the subject. Expert research was conducted with practitioners and theoreticians from the Lodz Province about chatbots, voicebots and public institutions. The research technique was a standardized interview. Findings: The results of the research made it possible to identify the opportunities, limitations and risks of implementing chatbots and voicebots in a public institution. Research limitations/implications: The survey conducted with experts indicates the problem and the need for change and identifies a way forward for digitization in public institutions. Practical implications: The results of the expert research can provide a path to the successful digitization of many public institutions and consequently provide inspiration and savings when designing bots that serve clients. Social implications: The quality of customer service of public institutions is a problem identified in this article. By implementing the suggestions resulting from the research, client service can be improved or completely reorganized. Originality/value: The article highlights the possibility of transferring artificial intelligence tools, i.e. chatbots and voicebots, to public institutions, also pointing out the possibilities of solutions and their limitations and risks of implementation. For the purpose of the paper, expert practitioners and theoreticians were invited to express their opinions.

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A Framework on botnet detection and forensics

Singh Harvinder, Bijalwan Anchit

Annals of Computer Science and Information Systems

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2017

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Vol. 10

93--101

EN

The utilization of Internet on domestic and corporate front has been increasing at drastic rate. Each organization and enterprise exploits the internet to its fullest extent based on its requirements. In almost all areas, internet is proved to be a boon. But sometimes it lands the users into trouble because of unwanted and uninvited harmful software applications. There are so many types of threats and challenges that are faced by the internet users. Out of all the threats faced by internet users, botnets are at the top most position. Because of these prodigious threats botnets are the rising area of research. Botnet works as a coordinated or synchronized activity where different bots collectively participate to perform a malicious task. The botnet is different from other form of malware in its capability to compromise the computer systems or smartphones to set up a link with command and control(C\&C) server controlled by bot controller. Because of the massive participation of compromised machines the losses caused by botnet attack are immeasurable. As a result, different researchers are showing keen interest in the field of botnets. The trend reflects that the number of researches in this field have gone up at tremendous rate in past 5 to 10 years. The present paper proposes a framework to systematically identify the presence of malicious bot, prevent it from spreading further and performing its forensic investigation.

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Applying artificial intelligence algorithms in MOBA games

Wiśniewski M., Niewiadomski A.

Studia Informatica : systems and information technology

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2016

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Vol. 1-2(20)

53--64

EN

Multiplayer Online Battle Arena games focus mainly on struggles between two teams of players. An increasing level of cyberbullying [1] discourages new players from the game and they often chose a different option, that is, a match against opponents controlled by the computer. The behavior of artificial foes can be dynamically fitted to user’s needs, in particular with regard to the difficulty of the game. In this paper we explore different approaches to provide an intelligent behavior of bots basing on more human-like combat predictions rather than instant, scripted behaviors.