Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/162918
Title: Singapore-based urban knowledge graph with site selection application
Authors: Hong, Glenda Zixuan
Keywords: Engineering::Computer science and engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Hong, G. Z. (2022). Singapore-based urban knowledge graph with site selection application. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/162918
Abstract: In recent years, knowledge graphs (KGs) have seen a rise in popularity, with major organisations jumping on the trend to create their own KGs. This is no surprise given the advantages that KGs have over other data models and the huge role they play in knowledge-driven machine learning paradigms. An interesting subset of KGs is urban KGs (UrbanKG), which are KGs developed from multi-source urban data. These UrbanKGs can be used to tackle urban machine learning tasks, an example of this being site selection within an urban city. This project aims to bring KGs and its applications to a Singapore context. Through the course of this project, a Singapore-based UrbanKG, centred around businesses in Singapore, was constructed. Additionally, to demonstrate a possible application of the UrbanKG, a site selection machine learning model and web application was also developed.
URI: https://hdl.handle.net/10356/162918
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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