| 摘要: |
| 目的 实现用户研究中语言材料分析的半自动化。方法 首先通过文献研究，明确了访谈类语言材料以性质分析为主要方法，问卷调查和网络评价类语言材料以量化统计分析为主要方法。然后通过方法比较，总结人工智能语义分析技术对于用户研究语言材料的八种常用能力：中文分词、命名实体识别、相似度分析、词频统计、情感倾向分析、文本分类、信息抽取、自动文摘，以及总结了以此为基础的语料分析处理流程。最后以“某品牌微蒸烤一体机交互设计创新”项目为例，介绍了应用人工智能语义分析技术对用户研究中的语言材料进行分析的具体执行方法。结果 测试验证人工智能语义分析技术在用户研究中的应用的有效性。结论 在设计领域应用人工智能技术具有巨大的潜力，通过总结针对性的算法，可以引入人工智能技术替代部分需要人智分析的工作，从而提高工作效率。 |
| 关键词: 用户研究 人工智能 语义分析 |
| DOI：10.19554/j.cnki.1001-3563.2020.18.007 |
| 分类号:TB472 |
| 基金项目:广州美术学院学术提升计划项目（20XSC43） |
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| Application of Artificial Intelligence Semantic Analysis Techniques in User Research |
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LIU Zai-xing, LIU Yi, GAO Xun
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Guangzhou Academy of Fine Arts, Guangzhou 510260, China
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| Abstract: |
| The paper aims to semi-automate the analysis of linguistic material in user research.Through the literature study,it wasclarified that qualitative analysis was the main method for interview-type language materials.Quantitative sta-tistical analysis was the main method forlanguage materials from questionnaires and web-based evaluation. Then, by comparing the methods, eight common capabilities of AI semantic analysis techniques for user study language materials weresummarized: Chinese words segmentation, identity of named entity, similarity analysis, word frequency statistics, sentiment analysis, text classification, information extraction, automatic abstraction. This paper summarizedthe semantic data analysis processing flow based on this approach. With the “Interaction design innovation of a brand of micro-steaming machine” as an example, it introducedthe specific implementation method of using artificial intelligence semantic analysis technology to analyze language materials in user research. The effectiveness of applying artificial intelligence semantic analysis techniques in user research was tested and verified.The application of AI technology in design has great potential.By summarizing the targeted approach, AI technology can be introduced to replace some of the tasks that require human intelligence analysis and improve efficiency. |
| Key words: user research artificial intelligence semantic analysis |
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