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This program constructs an inverted index for the purposes of information retrieval. The index is sorted by documentID and displays document frequency for each term and term frequency for each posting.
Sentiment Analysis have been done on twitter data regarding stock market using Naive Bayes Classifier. We have tested a few feature selection techniques to improve the accuracy of Naive Bayes Classifier. The feature selection techniques tested are: TF-IDF, Word Frequency, Document Frequency, Sparsity Reduction and Chi Square Statistics. The code…
An OpenMP based solution for computing K-most frequent words in a corpus (see README for more). Also, my submission for Assignment 2 of Parallel Computing Course, BITS Pilani (2nd Sem 2017/18)
Welcome to my News Summarizer project! This project scrapes news articles from famous news engines and aims to summarize the top-most articles through sentence fragmentation, keyword identification and weighted words in the text.