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5 votes
Accepted

How could facts be distinguished from opinions?

I will be starting my PhD in natural language processing in a few days and this is very similar to my proposed topic. It's an open problem that ties NLP and AI into philosophy of science and ...
primussucks's user avatar
5 votes
Accepted

How does the "Lorem Ipsum" generator work?

Lorem ipsum generators don't typically use anything considered as AI. Usually they just store large pieces of text and select sections from it randomly - they are very simple. The main goal is to ...
Neil Slater's user avatar
  • 32.1k
3 votes

How do I use GPT-2 to summarise text?

In short: It depends. Where will you run it? On Premises: You may want want to run in your own environment. IaaS: GPT models are often too big, so people might prefer to setup a different server for ...
Andre Goulart's user avatar
3 votes
Accepted

What is easier or more efficient to summarize voice or text? [DP/RN]

Summarizing text is always going to be 'easier or more efficient' than voice simply because voice requires the additional step of converting to text. That doesn't tell you anything about accuracy. ...
Brian O'Donnell's user avatar
3 votes

How does the "Lorem Ipsum" generator work?

If you wanted to generate more I guess you could take the string and convert to a list then you could randomly select as many words as you want, from the list. Using Python ...
Axle Max's user avatar
  • 131
2 votes
Accepted

How would one go about generating *sensible* responses to chat?

This seems like a problem for the use of an encoder-decoder pair such as those seen in text summarization (see this paper by Rush et al.: https://arxiv.org/pdf/1509.00685.pdfï%C2%BC). You would need ...
JMed's user avatar
  • 76
2 votes

Can abstractive summarization be achieved using neural networks?

The ability to re-frame summarization as a problem for ANN is rather dependent on what kind of output you're looking for: you mentioned 'salient parts of the text'. One possibly is to use a deep ...
NietzscheanAI's user avatar
2 votes

What are the most effective methods and tools for summarizing long-form content like articles, editorials, and discussion threads for an app?

I have out-of-date experience of working in this field, but I thought it might be useful to give an answer based on what I was doing approximately 10 years ago just to give background to any other ...
occipita's user avatar
  • 131
2 votes

Can I pick up possible calendar events from a text file

If you're fine training a model of your own, I would suggest try building a NER prediction model on your data. It would help to start with a certain type of data which follows similar pattern ...
Ashwani Yadav's user avatar
2 votes

Algorithms and strategies to help judges rule cases

Genuine success in this area would be beyond the state-of-the-art in research, since it likely requires analogising from relational knowledge extracted from text. In recent years, techniques for ...
NietzscheanAI's user avatar
2 votes
Accepted

How can LLMs understand and perform meta tasks? (e.g. summarization)

Well, you have to think that LMM are just next-token-predictors, so if you let it read a lot of text from the web/textbooks, probably they will learn that after "Be brief" there is a ...
Alberto's user avatar
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1 vote

Can you automatically write a text summarizing a finance document using AI models?

I think it is a quite reasonable task. To extract text from a PDF there are many libraries. If you also have images or other plots could be transformed in an embedding using a detector followed by ...
Ciodar's user avatar
  • 400
1 vote

Is it possible to classify the subject of a conversation?

This is a difficult problem. First, how do you define 'subject'? Do you have a (closed) lists of labels you want to assign? What about subjects that overlap, or don't occur in your list? What even is ...
Oliver Mason's user avatar
  • 5,387
1 vote

NLP Identifying important key words in a corpus

I am sure there are complex methods to extract keywords, but the standard one which should serve as a strong baseline is the RAKE graph algorithm https://pypi.org/project/rake-nltk/. It should work ...
saiRegrefree's user avatar
1 vote

How to add a pretrained model to my layers to get embeddings?

I think you should use Keras embedding layer. It will be too easier than what you are doing. Steps Create Embedding Matrix add matrix to embedding layer while building model. You will find detailed ...
PSKP's user avatar
  • 111
1 vote

What should the dimension of the input be for text summarization?

Briefly: I think what you are looking for is an RNN network (Either LSTM or GRU) with the many-to-many topology. Explanation: Clearly your input is the sentences (or to be more precise, the an ...
Alireza's user avatar
  • 405
1 vote
Accepted

How would you build an AI to output the primary concept of a paragraph?

Identifying the primary concepts of a paragraph required understanding of the meaning of the text. In natural language processing, we are still a long way off even recognising and representing the ...
Oliver Mason's user avatar
  • 5,387
1 vote
Accepted

Solution to classify product names

If you're looking for an existing solution, the best approach I found was using a TF-IDF model, check out the links below which have similar examples which should be easily adapted for your dataset. ...
Dan Pavlov's user avatar
1 vote
Accepted

Video summarization similar to Summe's TextRank

From "Deep learning-based video summarization — A detailed exploration" by Surya Remanan: Video summarization can be considered as the process of distilling a raw video into a more compact ...
Gokul Alex's user avatar
1 vote

What AI service can define personality portfolio based on text?

My first recommendation would be before you create an AI or ML based solution. Kindly consider using a business Q&A Software such as Questions for Confluence by Atlassian among others. An ...
Seth Simba's user avatar
  • 1,186

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