摘要
对基于人工智能技术的微信平台信息采集模型进行了研究,以图书馆为例设计了微信平台信息采集系统,并对其核心的图书推荐功能模块进行了详细设计。首先,对微信平台信息采集系统的整体框架和功能模块进行了设计;然后对图书推荐系统进行了研究与设计,提出一种基于点击率的图书推荐模型,对用户点击图书的概率进行计算,对用户可能点击的图书进行预测,继而实现图书精准推荐;最后分别对图书推荐系统和微信平台信息采集系统进行了实验与测试,实验结果表明:采用的基于提升决策树模型的图书推荐系统综合性能最好,平均绝对误差为1.755,均方误差为1.932,均方根误差为1.841,能够更为准确地对用户可能点击的图书进行预测,继而实现精准有效地向用户推荐满足其需求和喜好的图书;与微信APP成功对接后的图书馆微信公众号能够正常运行,微信平台信息采集系统性能良好,满足用户快速获取图书馆相关信息、提高图书馆信息服务质量的要求,具有一定参考价值。
The information collection model of WeChat platform is studied based on artificial intelligence technology.Taking a library as an example,a WeChat platform information collection system is designed,and its core book recommendation function module is designed in detail.Firstly,the overall framework and functional modules of the WeChat platform information collection system were designed;Then,the book recommendation system was studied and designed,and a book recommendation model based on click through rate was proposed to calculate the probability of users clicking on books,predict the books that users may click on,and then achieve accurate book recommendation;Finally,the book recommendation system and WeChat platform information collection system are tested and tested respectively.The experimental results show that the book recommendation system based on the lifting decision tree model in this paper has the best comprehensive performance,with an average absolute error of 1.755,a mean square error of 1.932,and a root mean square error of 1.841,which can more accurately predict the books that users may click,Then achieve precise and effective recommendation of books that meet users'needs and preferences;The library's WeChat official account can operate normally after the successful connection with WeChat APP,and the WeChat platform information collection system has good performance,which can meet the requirements of users to quickly obtain library related information and improve the quality of library information service,and has certain reference value.
作者
李金
张玲
LI Jin;ZHANG Ling(Yulin University,Yulin Shaanxi 719000,China)
出处
《自动化与仪器仪表》
2024年第2期11-14,19,共5页
Automation & Instrumentation
基金
榆林市2022年科技计划《陕北旱区旱作农业数字研究平台》(CXY-2022-68)。
关键词
人工智能技术
微信平台
信息采集
图书推荐
artificial intelligence technology
WeChat platform
information collection
book recommendations
