Difference between revisions of "Automatic Text Summarization (State of the art)"

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== "Standard" measure: ==
 
== "Standard" measure: ==
  
== "Standard" datasets: ==
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== Available summmarization datasets: ==
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|-
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! Dataset
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! Reference
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! Number of texts
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! Dataset Link
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! List of state-of-the-art results
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!Comments
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| Newsroom
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| Grusky et al. (2018)<ref>[https://doi.org/10.18653/V1/N18-1065 Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies]</ref>
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| https://summari.es/
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== "Standard" datasets: ==
 
{{StateOfTheArtTable}}
 
{{StateOfTheArtTable}}
  

Revision as of 09:41, 2 December 2019

"Standard" measure:

Available summmarization datasets:

Dataset Reference Number of texts Dataset Link List of state-of-the-art results Comments
Newsroom Grusky et al. (2018)[1] https://summari.es/



"Standard" datasets:

System Name Short Description Main Publications Software (if available) Results Comments (i.e. extra resources used, train/test times, ...)
SystemName How does it work? Author and Article [1] Software? 98% according to... Any extra comments?