Text Summary tool - a project which was part of Artificial Intelligence course at BITS Pilani

Calculates the most important words of given documents.

Discovering Mathematical Objects of Interest - A Study of Mathematical Notations

A Mini Search Engine in C++, using an inverted index and a trie.

Implementation of a search engine using a vector space model.

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)

In this project I am using the tf - idf algorithm and cosine similarity to find the similarity of two strings.

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.

A simple experiment with TFIDF in Python

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…

Keywords network builder based on TF-IDF with the use of Hadoop platform

A shared memory implementation of the DF (Document Frequency) index data structure for Linux file system using openMP threads.

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.