Abstract E-Rickshaw provides environment friendly, in-expensive, time-effective, suitable mode of transportation and plays a vital role in cities. lacks regularization, frequency management, which increases the burden on management system. Paper aims at developing real-time RFID based Management System for small scale farmers, focuses scheduling e-rickshaw according to passenger demand real tim...

Apache Spark is an open-source cluster computing framework. It has emerged as the next generation big data processing engine, overtaking Hadoop MapReduce which helped ignite the big data revolution. Spark maintains MapReduce’s linear scalability and fault tolerance, but extends it in a few important ways: it is much faster (100 times faster for certain applications), much easier to program in d...

Collaborative filtering based recommender systems use information about a user’s preferences to make personalized predictions about content, such as topics, people, or products, that they might find relevant. As the volume of accessible information and active users on the Internet continues to grow, it becomes increasingly difficult to compute recommendations quickly and accurately over a large...

Big Data has become a hot topic across several business areas requiring the storage and processing of huge volumes of data. Cloud computing leverages Big Data by providing high storage and processing capabilities and enables corporations to consume resources in a pay-as-you-go model making clouds the optimal environment for storing and processing huge quantities of data. By using virtualized re...

Frequent Itemset Mining is an important data mining task in real-world applications. Distributed parallel Apriori and FP-Growth algorithm the most that works on for finding frequent itemsets. Originally, Map-Reduce algorithm-based itemsets Hadoop were resolved. For handling big data, comes into picture but implementation of does not reach expectations distributed because its high I/O results tr...