融合用户和区位资源特征的混合房源推荐方法  

Hybrid Housing Resource Recommendation Based on Combined User and Location Characteristics

作　　者：朴勇[1] 朱锶源 李阳 PIAO Yong;ZHU Si-yuan;LI Yang(School of Software,Dalian University of Technology,Dalian,Liaoning 116620,China)

机构地区：[1]大连理工大学软件学院,辽宁大连116620

出　　处：《计算机科学》2022年第S01期733-737,共5页Computer Science

摘　　要：随着时代的发展,用户购买房屋的观念也在发生改变,在决策过程中更加注重房屋的区位资源。文中给出一种融合用户和区位资源特征的混合推荐方法,通过层叠式的方式将基于内容的推荐算法和基于用户的协同过滤算法相组合,通过用户兴趣偏好与区位资源的融合,提供更准确的房源推荐。通过整合17万余条房源交易数据和上千条区位资源数据,实验结果表明,该方法相比传统模型具有更好的推荐效果。With the development of the times,the idea of users to purchase houses has also changed,paying more attention to the location resources in their decision-making process.This paper proposes a hybrid recommendation method based on user and location resource characteristics to provide more accurate purchasing suggestions,where the content-based recommendation algorithm and user based collaborative filtering algorithm are combined in a cascade way.By integrating 170000+housing transaction with 1200+location resource data,experiment result shows that the proposed hybrid model has better recommendation effect than the traditional ones.

关 键 词：混合推荐模型 区位资源 用户兴趣偏好 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]