<p>you can use two approaches:</p>
<p>1- rule based (extract common words in each tag and classify documents with them)</p>
<p>2- machine learning</p>
<p>if you have a large scale training data you can use machine learning to classify documents:</p>
<p>you can use this approaches:</p>
<p><a href="https://arxiv.org/abs/1904.08398" rel="nofollow noreferrer">https://arxiv.org/abs/1904.08398</a></p>
<p><a href="https://medium.com/@armandj.olivares/using-bert-for-classifying-documents-with-long-texts-5c3e7b04573d" rel="nofollow noreferrer">https://medium.com/@armandj.olivares/using-bert-for-classifying-documents-with-long-texts-5c3e7b04573d</a></p>
How can I tag or give a document of text a topic?
<p>I have set of documents and corresponding set of tags for those documents</p>
<p>ex.</p>
<p>Document-&quot;Learned Counsel appearing for the Appellants however points out that in the..etc etc&quot;</p>
<p>Tags - &quot;Compensation, Fundamental Right&quot;</p>
<p>Now I have multiple documents with their corresponding tags and I another test set of data without any tags what NLP techniques do I use to give these documents tag? Do I use text classification or topic modeling can someone please guide or suggest some ideas.</p>