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基于协同过滤技术的室内设计项目推荐方法 被引量:2

Method of Interior Design Project Recommendation Based on Collaborative Filtering Technology
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摘要 针对当前室内设计项目推荐精度、执行效率低的难题,以改善室内设计项目推荐结果为目标,提出了基于协同过滤技术的室内设计项目推荐方法。首先分析当前国内外室内设计项目推荐的研究现状,找到各种室内设计项目推荐方法的不足,然后提取室内设计用户、项目特征,并设计了相似度度量计算公式,并根据k个最近邻用户对项目的预测评分得到室内设计项目推荐结果,最后与其它室内设计项目推荐方法进行了对照实验,分析其有效性和优越性,结果表明,文中方法的室内设计项目推荐精度超过95%,执行时间很短,加快了室内设计项目推荐速度,推荐结果明显好于其它室内设计项目推荐方法,解决了当前室内设计项目推荐过程中存在的缺陷。 Aiming at the problem of low precision and efficiency of interior design project recommendation,and aiming at improving the results of interior design project recommendation,a collaborative filtering technology based interior design project recommendation method is proposed.First of all,this paper analyzes the current research status of domestic and foreign interior design project recommendation systems,finds out the shortcomings of various current interior design project recommendation methods,then extracts interior design users and project characteristics and designs similarity measurement calculation formula,and obtains the recommendation results of interior design projects according to the prediction scores of k-nearest users for the project purpose,and finally recommends with other interior design project methods.A comparative experiment is carried out to analyze its effectiveness and superiority.The results show that the recommended accuracy of the method in this paper is more than 95%,the implementation time of the recommended method of the interior design project is very short,the recommended speed of the interior design project is accelerated,the recommended result of the interior design project is obviously better than other recommended methods of the interior design project.The current recommended method of the interior design project is solved defects in the process.
作者 宁云智 NING Yunzhi(Rail Transit Electic Service Technical College, Hunan Railway Professional Technology College, Zhuzhou 412001, China)
出处 《微型电脑应用》 2020年第11期123-125,共3页 Microcomputer Applications
关键词 协同过滤技术 室内设计 推荐方法 相似度度量 执行效率 collaborative filtering technology interior design recommendation model similarity measurement execution efficiency
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