Mining functional region of Singapore for smart city

• Main Author: Tan, Kok Wai
• Other Authors: Cong Gao
• Format: Final Year Project
• Language: English
• Published: 2017
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing
• Online Access: http://hdl.handle.net/10356/70365
• Institution: Nanyang Technological University

For the past years there had been an increasing popularity of social media among the population in Singapore, which resulted in the collection of large spatial temporal data sets and the opportunity of discovering useful information related to regional trends. Understanding the different regions in Singapore plays a key role in mining regional trends. In this project, an approach is proposed to analyze the content of the data sets for different regions of Singapore, focusing on English content only. First off, identify the different regions in Singapore. (i.e., west region, central region, etc) followed by segmenting each region into different sub-regions. Each sub-region was further segmented into different categories. (i.e., residential, business or commercial) Next, the data sets were categorized into different regions and categories and were displayed on Google Map. Finally, a list of top 25 words was generated, k-means clustering was performed on the data sets with silhouette analysis.