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How do you create list of sentences from the article? How do you know where article starts and what is just navigation or fluff.
Hi, We used a python library called newspaper to do it.
I found this really useful for my articles. The short snippets would work well as tweets, a tweet bot for article summaries would be cool!
We are glad that you liked it. That's a very good suggestion. By tweet bot, you mean when someone tweets an article link to the bot, it would respond back with the summary of that article, right? Thank you very much for taking the time to use the app and provide your feedback.
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Ah right, thank you for the detailed explanation. Currently, we are processing the text using a Python backend. In order to process it on the user's side, I guess we'll have to use Javascript. I will try to fix that in the next version. Thank you very much.
You don't need to move anything to the client side, what you're doing is covered under fair use doctrine.
Plus moving it to the client side would free up whatever resources they are currently using to feed summary info to us.
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> But we aren't storing any information on our servers, just showing selected sentences to the user. If this is in reference to the copyright comment, it doesn't matter -- you're still transmitting/redistributing the content, which is what matters. One way to get around this is to ship the code and have the code execute on the user's machine (i.e. what you're presumably doing with the extension).
you're still transmitting/redistributing the content Parts of it. Google does the same in their search results. The user can even decide which parts, because they show you the part that contains the search term. So they provide a service that includes storing your content in it's entirety. Has this ever been tested in court?
I think it is a good summarizer, I also saw a few others cited in the comments. Has anyone seen one that is a browser add-in where if I am surfing around and see a long article but don't have time to read it I can click a button without copying and pasting the link ?
Hi, We are glad that you liked it. We also have a chrome extension which does exactly as you say - https://chrome.google.com/webstore/detail/tldr-this-free-aut... Thank you very much for taking the time to use the app and provide your feedback.
Hi everyone I am delighted to share my new project "TLDR This" with you guys. Problem : There's so much content out there but too little time to read. So many times, it happens that there's a long article that we're interested in, but we don't really feel like scouring through it to extract relevant information from it. Hence, I created "TLDR This" to help you navigate relevant content quickly and easily, without hav…
Introduce this article: https://johnnyrodgers.is/burnout Each section subtitle is displayed as a sentence. Could you maybe ML generate a 1 sentence summary for section? I don't think there is an ML which could extract the take aways from each section and make a summary correctly, but that was my original expectation when I saw it first time.
There's plenty of abstractive and extractive methods for text summarization. In fact, that's what I'm working on right now, is to develop a news article summarization system for longer articles.
If you're interested in learning more, there's an excellent survey paper on ArXiv: https://arxiv.org/abs/1812.02303
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Thanks but that is not what the OP is claiming. That generates text from a seed, the OP is talking about an article that generates a summary of an article, but without using existing sentences.
Did you read the paper? https://d4mucfpksywv.cloudfront.net/better-language-models/l... You don’t need any seed, and can generate summaries (section 3.6). GPT-2 is the model to learn about if you’re interested in NLP.
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Did you read the paper? https://d4mucfpksywv.cloudfront.net/better-language-models/l... You don’t need any seed, and can generate summaries (section 3.6). GPT-2 is the model to learn about if you’re interested in NLP.
Are there any papers benchmarking a transformer NN architecture in comparison to something like a pointer-generator network? I'm doing a bit of work in this area (i.e. reimplementing papers), and I'm curious if GPT2-like models can derive greater semantic meaning.
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Introduce this article: https://johnnyrodgers.is/burnout Each section subtitle is displayed as a sentence. Could you maybe ML generate a 1 sentence summary for section? I don't think there is an ML which could extract the take aways from each section and make a summary correctly, but that was my original expectation when I saw it first time.
> I don't think there is an ML which could extract the take aways from each section There's plenty of abstractive and extractive methods for text summarization. In fact, that's what I'm working on right now, is to develop a news article summarization system for longer articles. If you're interested in learning more, there's an excellent survey paper on ArXiv: https://arxiv.org/abs/1812.02303