基于用户行为的智能档案推荐系统设计

Design of Intelligent Archives Recommendation System Based on Users’ Behavior

本文通过对档案管理系统的用户历史行为数据进行抽取、分析、预处理,设计了基于物品的协同过滤算法模型的档案智能推荐系统,可以在用户无法准确描述其需求时根据系统其他用户的历史行为数据智能推荐相关档案,从而在一定程度上解决了无法精准描述需求时的档案查询问题。

An intelligent archives recommendation system based on item collaborative filtering algorithm model is designed by extracting, analyzing and preprocessing the historical behavior data of users in the archives management system. When the users cannot accurately describe their needs, it can intelligently recommend related archives according to the historical behavior data of other users in the system, so it solves the problem of archives query when the requirements cannot be accurately described.