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Summarizing documents
--client
big_apple_py
--show
pygotham_2016
--room Room_CR4 11065 --force
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Marks
Author(s):
Mike Williams
Location
Room CR4
Date
jul Sat 16
Days Raw Files
Start
14:15
First Raw Start
14:12
Duration
00:55:00
Offset
0:02:30
End
15:10
Last Raw End
15:12
Chapters
00:00
0:27:00
Total cuts_time
54 min.
https://2016.pygotham.org/talks/226/summarizing-documents
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Description:
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Extractive summarization — finding the salient points in a document or corpus — is one of the most fundamental tasks in natural language processing. I’ll show you three ways to do it. One dates back to an IBM Journal article from 1958. One uses topic modeling, a technology from the 2000s. And one uses neural network-derived language embeddings and long short term memory networks — techniques that are only a couple of years old. I’ll explain the algorithms, show code and demos for all three, and I’ll discuss the engineering trade-offs.
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delay=1.0 But like you say, it's almost unnoticeable, and in any case it would be hard to improve without full screen of my face. Given that, I'm happy if you are!
2016-07-16/14_12_30.ts
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