Any good resources for learning algorithms in graph theory and bonus if incorporating NLP with graph theory?

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I’m taking a discrete math class now. Learned a ton of algorithms in graph theory. Find a solid textbook PDF online for free (Applied Discrete Structures is good), work through the problems, and watch this guy https://youtu.be/4ZlRH0eK-qQ

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No. But bump! And good luck!

What’s your end goals? It might be easier for recommending the right resources

End goals are to be able to know which algorithms to recommend when dealing with more than hundreds of unstructured text files on how to best group them and show the relationships between them. Sometimes clients want to see the relationship between the topics of each document, the references between each document, any relevant entities, which documents have the most connections/edges to determine priorities, and many more. This could be powerful for criminal investigation files and legal/regulatory files, as examples. I just want to know the options on analysis and how to best use them.

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