I am new to NLP and I would like to ask how can I extract sentences from the text based on keywords that I have using Python. I created a list of keywords which will be used to extract sentences from the document.
If this will be a simple tokenization problem in which you will loop the list through the tokens, how can I capture synonyms or related words?
Keyword: Internal business Sentence: You can only use this software for your business only. Keyword: Confidentiality Sentence: Information will be kept as secure as possible.
I actually implemented text categorization using TF-IDF, but with small dataset and large number of keywords. I don't think this will work to. Thanks in advance.
Is it possible to apply pre-trained models like word2vec?
Is it also possible to create a custom model that will fit my concerns?