Please use this identifier to cite or link to this item:
Title: Next point-of-interest recommendation
Authors: Tarjono, Kevin
Keywords: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Tarjono, K. (2022). Next point-of-interest recommendation. Final Year Project (FYP), Nanyang Technological University, Singapore.
Abstract: In the recent years, Next Point-of-Interest (POI) recommendation system has become more popular. The goal of POI recommendation system is to give POI recommendation to users given the users' historical check-in history. It is important to take into account the users recent check-in sequence and their preference to give accurate recommendations. This report proposes a POI recommendation model that utilizes multi-task learning that considers both the long-term preference and short-term preference of the users. The long-term component will learn about the user preference, and the short-term component will learn about the recent sequential check-in. The performance of the proposed model will then be compared to other baseline models to highlight the advantages of the proposed model.
Schools: School of Computer Science and Engineering 
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
  Restricted Access
655.76 kBAdobe PDFView/Open

Page view(s)

Updated on Oct 3, 2023


Updated on Oct 3, 2023

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.