scholarly journals Review: hindi question answering system using machine learning approach As an upshot of Natural Language Interface to Database (NLIDB), Question Answering System is relatively an Information Retrieval system which is suppose to reflect the user with the correct or closest results to the query being asked to the system in natural language. Information Retrieval and Information Extraction plays vital role in accomplishing the task of interaction between the user and the system. The paper discusses various ways and techniques of interaction between the user and the system along with different approaches. Machine Learning is one of the approaches which is preferred for the Question Answering System. Out of Supervised and unsupervised learning, supervised learning is taken priority here by going through numerous other techniques

Author(s):  
SHWETA MAHAJAN

There are plenty of social media webpages and platforms producing the textual data. These different kind of a data needs to be analysed and processed to extract meaningful information from raw data. Classification of text plays a vital role in extraction of useful information along with summarization, text retrieval. In our work we have considered the problem of news classification using machine learning approach. Currently we have a news related dataset which having various types of data like entertainment, education, sports, politics, etc. On this data we have applying classification algorithm with some word vectorizing techniques in order to get best result. The results which we got that have been compared on different parameters like Precision, Recall, F1 Score, accuracy for performance improvement.


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