Work

POI Recommendation Scheme Based on User Activity Patterns and Category Similarity

Year: 2024

Type: article

Abstract: The utilization of location-based social networks to provide point-of-interest (POI) recommendation services has been the subject of extensive research in recent years. Various factors that can enhance the precision of POI recommendations were examined in previous studies. However, the factors of a user, including the location and time, were not considered. In this paper, we proposed a POI recommendation scheme in which user activity patterns and the similarity of categories are considered. The proposed scheme is used to organize users based on the activity level and to take into account the characteristics of both the user and location. Furthermore, it provides personalized recommendations by considering the category similarity, time, and location data that were collected from users. We evaluated the performance of the proposed scheme and compared it with that of a currently used scheme. The proposed scheme exhibits precision that is approximately 16% greater than that of the existing scheme.

Source: Applied Sciences

DOI: 10.3390/app142310997

Authors: Jongtae Lim, Seoheui Lee, He Li, Kyoungsoo Bok, Jaesoo Yoo

Institutions: Chungbuk National University, Xidian University, Wonkwang University

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,728

Funders: National Research Foundation of Korea, Institute for Information and Communications Technology Promotion