Analysis Method of App Software User Experience Based on Multisource Information Fusion

IF 4.1 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal on Semantic Web and Information Systems Pub Date : 2023-06-27 DOI:10.4018/ijswis.325216

Yongquan Chen, Ying Jiang, Haiyi Liu

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引用次数: 0

Abstract

With the rapid development and popularization of intelligent terminals, app software has also developed rapidly. The research and practical value of mining user experience (UX) of app software form interaction information are becoming increasingly prominent. The interactive information of app software is multisource homogeneous and heterogeneous. In order to obtain more accurate and more comprehensive app software UX results, the fused multisource information should be analyzed. In this paper, the app software UX analysis method based on multisource information fusion is proposed. First, feature engineering is carried out to extract the features. Then, the feature combination tree is constructed after feature correlation mining. Finally, the multisource app software interactive data are fused, and the result is further analyzed to obtain the information of app software UX. The experiments clearly show that the method can effectively fuse multisource app software interaction data and help to comprehensively mine the app software UX embodied in the data.

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基于多源信息融合的App软件用户体验分析方法

随着智能终端的快速发展和普及，app软件也得到了快速发展。应用软件形式交互信息挖掘用户体验的研究和实用价值日益凸显。应用软件的交互信息是多源同质和异构的。为了获得更准确、更全面的app软件UX结果，需要对融合的多源信息进行分析。本文提出了一种基于多源信息融合的应用软件用户体验分析方法。首先，进行特征工程提取特征;然后，通过特征关联挖掘构建特征组合树。最后，对多源应用软件交互数据进行融合，并对结果进行进一步分析，得到应用软件的用户体验信息。实验清楚地表明，该方法可以有效地融合多源应用软件交互数据，有助于全面挖掘数据中蕴含的应用软件用户体验。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal on Semantic Web and Information Systems 工程技术-计算机：人工智能

CiteScore

6.20

自引率

12.50%

发文量

审稿时长

20 months

期刊介绍： The International Journal on Semantic Web and Information Systems (IJSWIS) promotes a knowledge transfer channel where academics, practitioners, and researchers can discuss, analyze, criticize, synthesize, communicate, elaborate, and simplify the more-than-promising technology of the semantic Web in the context of information systems. The journal aims to establish value-adding knowledge transfer and personal development channels in three distinctive areas: academia, industry, and government.