Abstract
The increase in use of NLP, throughout various domains has travelled its way upto legal environment in the recent years. The collection and analysis of data required in lawsuits and topic segmentation of the filed petitions into the respective categories electronically can reduce a significant amount of time and cost compared to human efforts. Our aim is to come up with the process of automating the Text Classification of documents. We plan to implement NLP techniques such as count Vectorizer along with TF-IDF and KNN to categorize the legal documents in a supervised environment. We have proposed a model which works on high dimensional data.
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