利用AI/ML算法分析IT系统用户行为的解决方案

IF 0.5 Q4 COMPUTER SCIENCE, THEORY & METHODS
O. Ņikiforova, Vitaly M. Zabiniako, Jurijs Kornienko, M. Gasparoviča-Asīte, Amanda Silina
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引用次数: 1

摘要

用户参与不足、缺乏用户反馈、用户需求不完整和不断变化是导致信息系统使用困难的一些关键原因,这可能会导致客户数量的减少。在前面作者的研究下,开发了分析IT系统用户行为的方法,旨在提高系统的可用性,从而提高业务流程的效率。所开发的方法基于图搜索算法、马尔可夫链和机器学习方法的使用。本文重点介绍了基于专家评估和不同用户体验分析情况的可视化演示的方法输出数据在定义其重要性的背景下的详细说明。本文简要介绍了该方法的本质,包括输入和输出数据集,并在专家的帮助下,根据其在用户体验分析中的重要性来评估预期结果。本文还介绍了为获取输出数据而开发的可视化原型,它允许验证输入/输出数据转换的可能性和预期的数据采集潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Solution to Analysis of IT System User Behaviour Using AI/ML Algorithms
Abstract Insufficient user involvement, lack of user feedback, incomplete and changing user requirements are some of the critical reasons for the difficulty of IS usage, which could potentially reduce the number of customers. Under the previous authors’ research, the method for analysing the behaviour of IT system users was developed, which was intended to improve the usability of the system and thus could increase the efficiency of business processes. The developed method is based on the use of graph searching algo rithms, Markov chains and Machine Learning approach. This paper focuses on detailing of method output data in the context of definition of their importance based on expert evaluation and demonstration of visual presentation of different UX analysis situations. The paper briefly reminds the essence of the method, including both the input and output data sets, and, with the help of experts, evaluates the expected result in the context of their importance in UX analysis. It also introduces visualization prototype developed to obtain the output data, which allows verifying the input/output data transformation possibilities and expected data acquisition potential.
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来源期刊
Applied Computer Systems
Applied Computer Systems COMPUTER SCIENCE, THEORY & METHODS-
自引率
10.00%
发文量
9
审稿时长
30 weeks
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