Difference between revisions of "IS428 2018 19T1 Group11 Proposal"

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<b> Data Attributes </b> <br>
 
<b> Data Attributes </b> <br>
 
The following is a snapshot of the data collected, and a description of the data attributes: <br>
 
The following is a snapshot of the data collected, and a description of the data attributes: <br>
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[[File:Metadata.jpg|thumb|alt=Alt text| Figure 1: Comments Dataset|center|upright=2.35]] <br>
  
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[[File:Intertopic.jpg|thumb|alt=Alt text| Figure 2: Inter-topic Distance Map split into Clusters based on Coherence Values|center|upright=2.35]] <br>
  
<b> </b>
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{| class="wikitable" style="background-color:#FFFFFF;" style="margin: auto;" width="60%"
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! Data Attributes
 +
! Description of attributes
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|-
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| style="text-align: center;" |Document
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| Comments scraped may consist of more than a sentence each. They are hence separated and identified by documents. Hence, a document represents a sentence of comment.
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|-
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| style="text-align: center;" | Dominant_Topic
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| Dominant topic refers to the cluster that the topic will most likely be sorted into.
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|-
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| style="text-align: center;" | Topic_Perc_Contrib
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| The probability that the comment will be found in the cluster amongst all other comments with similar keywords.
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|-
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| style="text-align: center;" | Keywords
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| Keywords that can be found in the specific cluster.
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|-
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| style="text-align: center;" | Text
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| Words in each comment after the removal of stop words (eg. the, is, to, on etc).
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|-
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| style="text-align: center;" | Original_Comment
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| Original comment sentence that was scraped.
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|-
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| style="text-align: center;" | Date
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| Date that the comment was posted.
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|}
 
<b> </b>
 
<b> </b>
 
<b> </b>
 
<b> </b>

Revision as of 00:08, 3 October 2018

Grab-logo.png


HOME PAGE

 

TEAM

 

PROPOSAL

 

POSTER

 

APPLICATION

 

RESEARCH PAPER

 

Version 1 | Version 2

INTRODUCTION

Write something here

MOTIVATION

Paragraph 1

Paragraph 2

Sub Paragraph 2.1

OBJECTIVES

Paragraph 1

  1. Number 1
  2. Number 2
DATA SOURCE

"Where our data came from"

Data Source
Data used is obtained from web scraping of various social media platforms such as Instagram, Twiiter, Reddit and Google Playstore.
The data set consists of 9000 comments that were scraped and collected.

Data Attributes
The following is a snapshot of the data collected, and a description of the data attributes:

Alt text
Figure 1: Comments Dataset


Alt text
Figure 2: Inter-topic Distance Map split into Clusters based on Coherence Values


Data Attributes Description of attributes
Document Comments scraped may consist of more than a sentence each. They are hence separated and identified by documents. Hence, a document represents a sentence of comment.
Dominant_Topic Dominant topic refers to the cluster that the topic will most likely be sorted into.
Topic_Perc_Contrib The probability that the comment will be found in the cluster amongst all other comments with similar keywords.
Keywords Keywords that can be found in the specific cluster.
Text Words in each comment after the removal of stop words (eg. the, is, to, on etc).
Original_Comment Original comment sentence that was scraped.
Date Date that the comment was posted.

BACKGROUND SURVEY OF RELATED WORKS
Related Works What We Can Learn
Grab Traffic Trends

"Insert Image here" Source: "Insert source here"

  • Learning 1
  • Learning 2
  • Learning 3
Another Graph

"Insert Image here" Source: "Insert source here"

  • Learning 1
  • Learning 2
  • Learning 3
STORYBOARD
Sketches Description of Approach
Sketch 1

"Insert Image here" Source: "Insert source here"

  • Approach 1
  • Approach 2
  • Approach 3
Sketch 2

"Insert Image here" Source: "Insert source here"

  • Approach 1
  • Approach 2
  • Approach 3
PROPOSED VISUALISATION

???? Write what???? halps

KEY TECHNICAL CHALLENGES
  • Challenge 1
  • Challenge 2
  • Challenge 3
PROJECT TIMELINE

"Insert Gantt Chart"

REFERENCES

"Insert Links and Description"

COMMENTS

Something