摘要： 在基于B/S架构的信息管理系统使用过程中,必须完成大量表单数据的填写及录入,但目前其主要方式为手工录入,存在录入效率低和结果不准确等问题。为此,通过研究搜索引擎的实时预测功能和推荐系统,提出一种基于逆最近邻协同过滤的表单推荐录入模型。介绍模型体
系架构及执行流程,在此基础上设计改进的逆最近邻协同过滤算法,使用该算法获取基于用户行为的表单录入推荐结果,从而将个性化推荐应用于数据录入和表单填写领域。实验结果表明,该模型可有效提高数据录入效率和录入结果的准确率。
关键词:
数据录入,
表单填充,
协同过滤,
逆最近邻,
推荐录入模型
Abstract: In the process of using the information management system based on B/S structure,users are facing a lot of forms to fill in and data to entry during use.But the traditional methods of form filling and data entry are always by manual,which causes many problems such as low input efficiency and inaccurate entry.Through the study of real-time prediction capabilities of search engines and recommendation system,this paper proposes a recommended entry model based on Reverse Nearest Neighbor(RNN) collaborative filtering.It introduces the architecture and implementation process,and based on this,proposes an RNN collaborative filtering algorithm.By using this algorithm to obtain recommended results
which are based on user behavior,the personalized recommendation can be applied to the field of data entry and form filling.Experimental results show that the proposed model can effectively improve the efficiency of the data entry and accuracy of the entry results.
Key words:
data entry,
form filling,
collaborative filtering,
Reverse Nearest Neighbor(RNN),
recommended entry model
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