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Title: Next point of interest (POI) recommendation
Authors: Wu, Ziqing
Keywords: Engineering::Computer science and engineering
Issue Date: 2020
Publisher: Nanyang Technological University
Project: SCSE19-0014
Abstract: Next Point-of-Interest (POI) Recommendation systems nowadays often assume that the users' check-in records are accurate. However, the accuracy and certainty of a user's check-in history may not be guaranteed in a real-world application due to various reasons. In order to make POI Recommendation systems overcome this problem, we first processed and analyzed real-world data to investigate the key influencer of users' decisions. This report then proposes a novel model that utilizes the users' past spatial and temporal information to predict users' intentions and offer them suggestions on where to go. Experiments were conducted on 3 sets of real-world data. The performance of the model was also compared with other baseline models to demonstrate the advantages of this model.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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