Difference between revisions of "1718t1is428T7 Research Paper"

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==<div style="background:#143c67; padding: 15px; font-weight: bold; line-height: 0.3em;letter-spacing:0.5em;font-size:20px"><font color=#fbfcfd face="Lato"><center>ABSTRACT</center></font></div>==
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As part of the Smart Nation initiative in Singapore, public data of Singapore is made available by Singapore government’s open data portal for the nation and decision makers to monitor and gain insights about Singapore’s social and economic trends. However, a proper tool to visualize these data is lacking. To address this need, we designed and developed GeViz, an interactive visual analytics dashboard for the public and ministries of Singapore to uncover insights on Singapore government's procurement data, with the aim to identify spending patterns based on procurement categories, goods and services procured and ministry and suppliers relationships. We leveraged on machine learning to classify procurement categories based on the tender description and adopted various visualization techniques to explore and analyse Singapore government’s procurement patterns.
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==<div style="background:#143c67; padding: 15px; font-weight: bold; line-height: 0.3em;letter-spacing:0.5em;font-size:20px"><font color=#fbfcfd face="Lato"><center>RESEARCH PAPER</center></font></div>==
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You can view our research paper here -
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[[File:IS428 Group7 GeViz Research Paper .pdf|thumb]]

Latest revision as of 00:08, 26 November 2018

Geviz.png


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ABSTRACT

As part of the Smart Nation initiative in Singapore, public data of Singapore is made available by Singapore government’s open data portal for the nation and decision makers to monitor and gain insights about Singapore’s social and economic trends. However, a proper tool to visualize these data is lacking. To address this need, we designed and developed GeViz, an interactive visual analytics dashboard for the public and ministries of Singapore to uncover insights on Singapore government's procurement data, with the aim to identify spending patterns based on procurement categories, goods and services procured and ministry and suppliers relationships. We leveraged on machine learning to classify procurement categories based on the tender description and adopted various visualization techniques to explore and analyse Singapore government’s procurement patterns.

RESEARCH PAPER

You can view our research paper here - File:IS428 Group7 GeViz Research Paper .pdf