网站用户行为分析及服务推荐研究  

Website user behavior analysis and service recommendation research

作　　者：张婉婷 赵敏[1] ZHANG Wanting;ZHAO Min(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《智能计算机与应用》2020年第2期71-74,共4页Intelligent Computer and Applications

摘　　要：本文运用基于物品的协同过滤推荐算法设计法律资讯信息推荐系统。介绍了该算法需要的数学理论知识,如相似度计算方法、系统评估方法和KNN算法等。详细解释了基于物品的协同过滤推荐算法及其具体实现步骤。最后构建法律资讯信息推荐系统并对系统做出评估。通过实验仿真分析,发现基于物品的协同过滤算法在物品种类丰富,用户个性化需求强烈的领域优势明显。其相关的推荐和解释利用用户的历史行为数据,结果让用户信服。This paper uses collaborative filtering recommendation algorithm based on items to design legal information recommendation system.Firstly,the paper introduces the theoretical knowledge of the algorithm,such as similarity calculation method,system evaluation method and KNN algorithm.Then,the paper explains the collaborative filtering recommendation algorithm based on items and its implementation steps in detail.Finally,the paper constructs a legal information recommendation system and evaluate the system.Through the experiment analysis,it is found that the collaborative filtering algorithm based on goods has obvious advantages in the fields of rich kinds of goods and strong personalized needs of users.Its relevant recommendation and interpretation make use of the historical behavior data of users,and the results are convinced.

关 键 词：协同过滤 相似度 KNN 法律资讯信息推荐系统 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]