Personalized Tourist Attraction Recommendation System Using Collaborative Filtering on Tourist Preferences

被引：0

作者：

Supanich, Weeriya ^{[1
]}

Kulkarineetham, Suwanee ^{[1
]}

机构：

[1] Rajamangala Univ Technol Tawan Ok, Fac Business Adm & Informat Technol, Dept Informat Technol, Bangkok 10400, Thailand

来源：

2022 19TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER SCIENCE AND SOFTWARE ENGINEERING (JCSSE 2022) | 2022年

关键词：

Travel recommendation system; Tourist attraction recommendation; Collaborative filtering;

D O I：

10.1109/JCSSE54890.2022.9836255

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

A recommendation system becomes a good assistant in filtering various information from diverse sources to perform a matching result to users. These systems can provide a list of recommendations personalized to user preferences and needs. Almost any business can benefit from a recommendation system, including the tourism industry. In this paper, A personalized tourist attraction recommendation system (PTARS) based on a collaborative filtering technique is proposed. The research objective is to find the best model to recommend a customized destination to a new target user based on their preferences and behavior by using a user's travel-related data source acquired by an explicit approach. Our research result exhibits that the best similarity measure that yields the most accurate result is Euclidean distance; that calculation was from the top 25 k-neighbor values.

引用

页数：6

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