For a given text, retrieve the associated topic and top N similar texts by Topic Modelling approach (LDA).

• For a given set of documents:

  • Find the ideal model parameters for topic modelling (LDA) i.e. number of topics, learning decay.
  • Generate document-word matrix with weightage of each word.
  • Generate topic-word matrix with number of words limited to each topic.

• Predict:

  • For a given text, retreive the best topic.
  • Get the dominant word in the predicted topic.
  • Dominant word ultimately is the topic tag

• Get similar douments:

  • For a given text, derive distance with all documents.
  • Get the top N documents based on distance.

• Predict a topic (dominant word associated to the topic) for a given text.
• Find N similar texts for a given text and documents.

https://medium.com/@yanlinc/how-to-build-a-lda-topic-model-using-from-text-601cdcbfd3a6