期刊目次

加入编委

期刊订阅

添加您的邮件地址以接收即将发行期刊数据:

Open Access Article

Advances in International Computer Science. 2023; 3: (5) ; 17-20 ; DOI: 10.12208/j.aics.20230046.

Research on the application of artificial intelligence and machine learning in internet software development
人工智能与机器学习在互联网软件开发中的应用研究

作者: 张春栋 *

Hoyoverse Singapore

*通讯作者: 张春栋,单位:Hoyoverse Singapore;

发布时间: 2023-12-22 总浏览量: 740

摘要

伴随着人工智能和机器学习技术的飞速进步,它们在互联网软件开发中的运用已经变成了提高工作效率、增进用户体验和促进创新增长的核心要素。人工智能技术以智能推荐系统,自然语言处理以及智能搜索引擎为手段向用户提供个性化服务,大大改善了用户体验。同时机器学习数据驱动的特点使开发者可以通过预测分析,用户行为分析及软件缺陷预测来提升开发效率及系统性能。自动化测试,代码生成这些技术对于减少人力成本,缩短上市时间也起到了至关重要的作用。另外,人工智能与机器学习相结合推动互联网软件开发创新并加速新产品研发周期。这些应用不但使软件变得更智能,而且给企业提供了不断增长的力量。

关键词: 人工智能;机器学习;互联网软件开发;用户体验;开发效率

Abstract

With the rapid progress of artificial intelligence and machine learning technology, their application in Internet software development has become a core element to improve work efficiency, enhance user experience and promote innovative growth. Artificial intelligence technology provides personalized services to users through intelligent recommendation system, natural language processing and intelligent search engine, greatly improving user experience. At the same time, the data-driven characteristics of machine learning enable developers to improve development efficiency and system performance through predictive analysis, user behavior analysis and software defect prediction. Automated testing and code generation technologies also play a crucial role in reducing manpower costs and shortening time to market. In addition, the combination of artificial intelligence and machine learning promotes innovation in Internet software development and accelerates the R&D cycle of new products. These applications not only make software more intelligent, but also provide enterprises with growing power.

Key words: Artificial intelligence; Machine learning; Internet software development; User experience; Development efficiency

参考文献 References

[1] 陈利. 人工智能在计算机软件开发中的运用[J]. 信息与电脑(理论版), 2023, 35 (12): 32-35.

[2] 曹越. 基于机器学习的软件开发者心智状态识别技术[D]. 南京大学, 2021.

[3] 张志武. 基于机器学习的软件缺陷预测方法研究[D]. 南京邮电大学, 2018.

[4] R·梅哈韦德,J·弗利克斯·德索扎,P·温卡塔·纳加·普纳·邦萨,等.基于人工智能和机器学习的产品开发.CN201810924101.6[2024-03-11].

[5] 李佳.人工智能背景下互联网金融专业人才培养模式的思考[J].中国教育信息化, 2021(7):3.

引用本文

张春栋, 人工智能与机器学习在互联网软件开发中的应用研究[J]. 国际计算机科学进展, 2023; 3: (5) : 17-20.