Flexible POI Recommendation based on User Situation

被引：1

作者：

Jang, Sein ^{[1
]}

Kim, Jeong-Hun ^{[2
]}

Nasridinov, Aziz ^{[2
]}

机构：

[1] Data Fus Res Ctr, Seoul, South Korea

[2] Chungbuk Natl Univ, Dept Comp Sci, Cheongju, South Korea

来源：

2019 INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA) | 2019年

关键词：

Point-of-Interesting (POI); POI Recommendation; Weight-Threshold Algorithm;

D O I：

10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00211

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Location-based social networks (LBSNs) become an essential part of our lives as these services can assist users in finding interesting point-of-interest (POI). Many studies have been conducted to perform POI recommendations with various factors, such as user's check-in records, geographic information, and social relationship. However, existing studies use only fixed values without considering the user's current situations that frequently change. In this paper, we propose a flexible POI recommendation based on the user's situation. For this, we first construct a graph model of three factors, such as trajectory, distance, and preference. We then use a weight-threshold algorithm (w-TA) to adjust the weight of each factor based on the user's current situation. The experiment results show the flexibility of the proposed method in various conditions.

引用

页码：1257 / 1260

页数：4

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