Parallel Multitasking In Real Time Applications

Abstract

Parallel multitasking is mainly for solving multiple related classification of tasks parallely. It classifies every sequence of data received by each task accurately and efficiently. Parallel multitasking also enables parallel micro-blogging on a group of users, which allows the user to post views as well as see the views posted by others. It maintains a global model over the entire data of all tasks. The individual models for multiple related tasks are jointly inferred by leveraging the global model through a parallel multitasking approach. The user can work on multiple applications at the same time. Experimental results shows that the method is effective and scalable at the online classification of multiple task