Co-Founder & CTO at BitSave • IIIT Hyderabad

Sajal Sarwar Sharma  • Peerlist

Project aimed to developing a search engine for Wikipedia corpus of 45GB with response time less than a second. Retrieval results included relevant documents from corpus for the query supplied by the user.

Tags:  Java, SAX Parser,  Wikiped

Wikipedia Search Engine

Sentiment analysis of sentences for hindi language.

The domain of the sentence is predicted by already calculated TF-IDF of the training sentences, the corresponding model is applied to the sentence once the domain is predicted, the corres

Analysing the sentiments of user input phrases/sentences (Hindi Language)

Implemented LDA model to find top k influential users and finding the topics they tweet about using mallet thus finding topics trending on twitter.

Topic Modelling in Social Media

Developed a sentiment analysis tool which takes dynamic tweets from twitter about a particular topic and performs analysis of sentiments dynamically plotting it live on graph to estimate the ups and downs of the topic in run time.

Tags: Ma

Twitter Sentiment Analysis

A database query engine based on SQL that performs basic query operations.

A simple database application that facilitates basic management of page, loading of pages to page buffer, insertion into database, select and create queries as well

Elementary Database Query Engine

The project aims to provide a website based on Web2py framework. It consists of 2 player chess game, one player can create a game and other can join it, many simultaneous games can be played and the game state can be saved as well, facility

Online Multiplayer Chess

It is an electronic version of musical instrument named “Harp”. It has LASERs emitting in place of strings, and when these LASERs are disturbed with fingers, corresponding nodes of the Harp are played. Won Intra University and Inter Univers

LASER Harp

Identifying the person with whom the input face corresponds to.

The input data(yalefaces) is divided into 80:20 split. 80% training data and 20% test data. PCA(Principal Component Analysis) was applied to reduce the dimensionality of the i