Analyze the rainfall of landslide on Apache Spark

Aim: To analyze the rainfall data from a given place using big data implementation for scalability for rainfall prediction Synopsis: In recent years countries like United States of America, Japan, China, Taiwan etc, were suffering from extreme and dangerous natural disasters due to impact of climate. The flood is one of the main reasons for […]

Characterizing and Countering Communal Microblogs During Disaster Events

Aim: The objective of this project is to develop a system to identify the tweet harbor hatred in micro blogs during disaster events. Existing System: The existing system uses sentiment analysis technique to identify the sentiment of the tweet. However this is not sufficient to identify the anti-social messages. The sentiment analysis might give the […]

Real-Time Prediction of Taxi Demand Using Recurrent Neural Networks

Aim: To predict the high demand need of pickup location for taxi services based on their previous history. Existing System: TAXI drivers need to decide where to wait for passengers in order to pick up someone as soon as possible. Passengers also prefer to quickly find a taxi whenever they are ready for pickup. The […]

Location Inference for Non-geo tagged Tweets in User Timelines

Aim: To obtain the information of user location from the tweet, which are not with the help of geo-tagged, but with the help of machine learning. Existing System: Business can obtain the geo location of their user with the geo-tagged content like images or tweets. But not all tweets were geo-tagged. The existing system depends […]

Leveraging Affective Hashtags for Ranking Music Recommendations

Aim: The aim of this project is to achieve the user personal Goal rather than merely performing Individual task by using mobile application. Existing System: Existing system uses manual intervention and usage based suggestion. The recommendation of any service is based on the number of users who already requested similar services on the same demographic. […]