A Collaborative Filtering Based Personalized TOP-K Recommender System for Housing

被引：0

作者：

Wang, Lei ^{[1
]}

Hu, Xiaowei ^{[1
]}

Wei, Jingjing ^{[1
]}

Cui, Xingyu ^{[1
]}

机构：

[1] Nanjing Forestry Univ, Dept Management Sci & Engn, Nanjing 210037, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF THE 2012 INTERNATIONAL CONFERENCE OF MODERN COMPUTER SCIENCE AND APPLICATIONS | 2013年 / 191卷

关键词：

personalized recommender system; preference; collaborative filtering; space vector; TOP-K;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Electronic information resource has become the main way for users obtaining information. Facing the huge amount of information in the real estate market, traditional methods are difficult to meet the users' effective information needs. How to dig out from the mass of information to the appropriate information is a difficult and time-consuming problem for anyone. How can personalized recommender system solve the problem? In this paper, the authors proposed an algorithm named Collaborative Filtering Based Personalized TOPK Recommender system for Housing (CFP-TR4H), and a personalized recommender system based on CFP-TR4H is also designed in this manuscript. A case study on Nanjing (a city in China) real estate market is also conducted to discuss and validate the effectiveness of our method.

引用

页码：461 / 466

页数：6

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