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I want to do SEMANTIC keyword search on list of topics with NLP(Natural Language Processing ). It would be very appreciable if you post any reference links or ideas.

user1632980
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  • Please consider marking the answer as accepted (grey tick mark on the left of the answer) and upvoting it if you find it useful. – sophros Feb 15 '21 at 10:27

1 Answers1

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Your questions is somewhat vague but I will try nonetheless...

If I understand you correctly then what you want to do (depending on the effort you want to spend) is the following:

  1. Expand the keyword to a synonym list that you will use to search for in the topics (you can use WordNet for this).

  2. Use collocations (n-gram model) to extend the keyword to the likely bi-, tri-grams and search for these in the texts.

  3. Depending on the availability of the data you may also want to create a classifier (e.g. using good old SVM or CRF) that maps list of keywords into topics (where topic is a class).

  4. Assuming that you have a number of documents per each topic, you may also want to create a list of most frequent words per topic (eliminating stop-words).

Most of the functionality is available via NLTK, Pandas, etc. for Python and OpenNLP, libsvm, LingPipe in Java.

sophros
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