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I am looking to extract the central theme from a given news headline using NLP or text mining. Is there any reference that goes in this direction?

Here's an example. Let's say that I have the following news headline.

BRIEF-Dynasil Corporation Of America Reports Q2 EPS Of $0.08

Then the algorithm should produce

Reports

Here's another example. The input is

China's night-owl retail investors leverage up to dominate oil futures trade

And the output would e.g. be

oil futures

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You could formulate the problem as a topic classification task, hence you need labeled data.

From an unsupervised point of view, you could represent sentences with some fixed feature vector (latent representation).

  1. Generating Sentences from a Continuous Space.
  2. Paragraph2Vec.

BRIEF-Dynasil Corporation Of America Reports Q2 EPS Of $0.08

China's night-owl retail investors leverage up to dominate oil futures trade

Self-attention models would be very useful to this kind of problems since you don't need to encode all the context in the last hidden cell of some RNN model to classify to which theme the headline belongs.

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