UX Framework Including Imbalanced UX Dataset Reduction Method for Analyzing Interaction Trends of Agent Systems
The performance of game AI can significantly impact the purchase decisions of users. User experience (UX) technology can evaluate user satisfaction with game AI by analyzing user interaction input through a user interface (UI). Although traditional UX-based game agent systems use a UX evaluation to...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/3/1651 |
| _version_ | 1797623149244710912 |
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| author | Bonwoo Gu Yunsick Sung |
| author_facet | Bonwoo Gu Yunsick Sung |
| author_sort | Bonwoo Gu |
| collection | DOAJ |
| description | The performance of game AI can significantly impact the purchase decisions of users. User experience (UX) technology can evaluate user satisfaction with game AI by analyzing user interaction input through a user interface (UI). Although traditional UX-based game agent systems use a UX evaluation to identify the common interaction trends of multiple users, there is a limit to evaluating UX data, i.e., creating a UX evaluation and identifying the interaction trend for each individual user. The loss of UX data features for each user should be minimized and reflected to provide a personalized game agent system for each user. This paper proposes a UX framework for game agent systems in which a UX data reduction method is applied to improve the interaction for each user. The proposed UX framework maintains non-trend data features in the UX dataset where overfitting occurs to provide a personalized game agent system for each user, achieved by minimizing the loss of UX data features for each user. The proposed UX framework is applied to a game called “Freestyle” to verify its performance. By using the proposed UX framework, the imbalanced UX dataset of the Freestyle game minimizes overfitting and becomes a UX dataset that reflects the interaction trend of each user. The UX dataset generated from the proposed UX framework is used to provide customized game agents of each user to enhanced interaction. Furthermore, the proposed UX framework is expected to contribute to the research on UX-based personalized services. |
| first_indexed | 2024-03-11T09:24:32Z |
| format | Article |
| id | doaj.art-d7bdb7c332704e97a25cfe0a4c37e6ef |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T09:24:32Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d7bdb7c332704e97a25cfe0a4c37e6ef2023-11-16T18:04:25ZengMDPI AGSensors1424-82202023-02-01233165110.3390/s23031651UX Framework Including Imbalanced UX Dataset Reduction Method for Analyzing Interaction Trends of Agent SystemsBonwoo Gu0Yunsick Sung1Department of Multimedia Engineering, Graduate School, Dongguk University-Seoul, Seoul 04620, Republic of KoreaDepartment of Multimedia Engineering, Dongguk University-Seoul, Seoul 04620, Republic of KoreaThe performance of game AI can significantly impact the purchase decisions of users. User experience (UX) technology can evaluate user satisfaction with game AI by analyzing user interaction input through a user interface (UI). Although traditional UX-based game agent systems use a UX evaluation to identify the common interaction trends of multiple users, there is a limit to evaluating UX data, i.e., creating a UX evaluation and identifying the interaction trend for each individual user. The loss of UX data features for each user should be minimized and reflected to provide a personalized game agent system for each user. This paper proposes a UX framework for game agent systems in which a UX data reduction method is applied to improve the interaction for each user. The proposed UX framework maintains non-trend data features in the UX dataset where overfitting occurs to provide a personalized game agent system for each user, achieved by minimizing the loss of UX data features for each user. The proposed UX framework is applied to a game called “Freestyle” to verify its performance. By using the proposed UX framework, the imbalanced UX dataset of the Freestyle game minimizes overfitting and becomes a UX dataset that reflects the interaction trend of each user. The UX dataset generated from the proposed UX framework is used to provide customized game agents of each user to enhanced interaction. Furthermore, the proposed UX framework is expected to contribute to the research on UX-based personalized services.https://www.mdpi.com/1424-8220/23/3/1651user experience and user interfaceimbalanced UX datasetartificial intelligencegame agent systemhuman–computer interaction |
| spellingShingle | Bonwoo Gu Yunsick Sung UX Framework Including Imbalanced UX Dataset Reduction Method for Analyzing Interaction Trends of Agent Systems Sensors user experience and user interface imbalanced UX dataset artificial intelligence game agent system human–computer interaction |
| title | UX Framework Including Imbalanced UX Dataset Reduction Method for Analyzing Interaction Trends of Agent Systems |
| title_full | UX Framework Including Imbalanced UX Dataset Reduction Method for Analyzing Interaction Trends of Agent Systems |
| title_fullStr | UX Framework Including Imbalanced UX Dataset Reduction Method for Analyzing Interaction Trends of Agent Systems |
| title_full_unstemmed | UX Framework Including Imbalanced UX Dataset Reduction Method for Analyzing Interaction Trends of Agent Systems |
| title_short | UX Framework Including Imbalanced UX Dataset Reduction Method for Analyzing Interaction Trends of Agent Systems |
| title_sort | ux framework including imbalanced ux dataset reduction method for analyzing interaction trends of agent systems |
| topic | user experience and user interface imbalanced UX dataset artificial intelligence game agent system human–computer interaction |
| url | https://www.mdpi.com/1424-8220/23/3/1651 |
| work_keys_str_mv | AT bonwoogu uxframeworkincludingimbalanceduxdatasetreductionmethodforanalyzinginteractiontrendsofagentsystems AT yunsicksung uxframeworkincludingimbalanceduxdatasetreductionmethodforanalyzinginteractiontrendsofagentsystems |