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DTSTAMP:20220512T210934Z
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DTSTART;TZID=Canada/Eastern:20220512T160000
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DESCRIPTION:Text summarization is a method for generating a summary of long
  texts by focusing on the sections that contain essential information whil
 e keeping the overall meaning intact. Its goal is to reduce the size of lo
 ng documents\, which would be difficult and expensive to process manually.
  With the current explosion of data circulating in digital space\, particu
 larly unstructured textual data\, there is a need to build tools that allo
 w people to extract insights from it. Taking notes is a popular practice f
 or many people employed in situations where it is essential to keep track 
 of what is said\, such as during an online lecture. The art of note-taking
  does not entail taking down every single word stated but rather broad sum
 maries of what is covered. Making succinct yet informative summaries is th
 e key to successful note-taking. In this seminar\, we will be discussing h
 ow we have used visualization and data storytelling techniques in our proj
 ect to make informed decisions. This project aims to address the difficult
 ies of note-taking by building an application that produces notes based on
  the transcripts generated by the Automatic Speech Recognition (ASR) techn
 ology of the meeting platforms. We relied on visualization concepts for th
 ree major decisions that would define our project as a whole. These decisi
 ons are the choice of online meeting platform\, preference of text summari
 zation model and the messaging platform choice.\n\nSpeaker(s): Manoj Varma
  Alluri\, \n\nToronto\, Ontario\, Canada\, Virtual: https://events.vtools.
 ieee.org/m/313207
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.o
 rg/m/313207
ORGANIZER:reza.dibaj@ieee.org
SEQUENCE:2
SUMMARY:Visualization Techniques in Text Summarization of Online Transcript
 s – Students’ Research in ML and DL at Durham College
URL;VALUE=URI:https://events.vtools.ieee.org/m/313207
X-ALT-DESC:Description: <br /><p>Text summarization is a method for generat
 ing a summary of long texts by focusing on the sections that contain essen
 tial information while keeping the overall meaning intact. Its goal is to 
 reduce the size of long documents\, which would be difficult and expensive
  to process manually. With the current explosion of data circulating in di
 gital space\, particularly unstructured textual data\, there is a need to 
 build tools that allow people to extract insights from it. Taking notes is
  a popular practice for many people employed in situations where it is ess
 ential to keep track of what is said\, such as during an online lecture. T
 he art of note-taking does not entail taking down every single word stated
  but rather broad summaries of what is covered. Making succinct yet inform
 ative summaries is the key to successful note-taking. In this seminar\, we
  will be discussing how we have used visualization and data storytelling t
 echniques in our project to make informed decisions. This project aims to 
 address the difficulties of note-taking by building an application that pr
 oduces notes based on the transcripts generated by the Automatic Speech Re
 cognition (ASR) technology of the meeting platforms. We relied on visualiz
 ation concepts for three major decisions that would define our project as 
 a whole. These decisions are the choice of online meeting platform\, prefe
 rence of text summarization model and the messaging platform choice.</p>
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