Browse

The Virtual University, Pakistan’s first University based completely on modern Information and Communication Technologies, was established by the Government as a public sector, not-for-profit institution with a clear mission: to provide extremely affordable world class education to aspiring students all over the country.

Using free-to-air satellite television broadcasts and the Internet, the Virtual University allows students to follow its rigorous programs regardless of their physical locations. It thus aims at alleviating the lack of capacity in the existing universities while simultaneously tackling the acute shortage of qualified professors in the country. By identifying the top Professors of the country, regardless of their institutional affiliations, and requesting them to develop and deliver hand-crafted courses, the Virtual University aims at providing the very best courses to not only its own students but also to students of all other universities in the country.

OPTIMIZATION OF SVM FOR SENTIMENT ANALYSIS

Download

Author: MUNIR AHMAD


Citable URI : https://vspace.vu.edu.pk/detail.aspx?id=124

Publisher : Virtual University

Date Issued: 5/28/2018 12:00:00 AM


Abstract

The growth of user’s generated contents increased exponentially onthe microblogging platforms like Facebook, Twitter and Blogger in the form of comments and opinions. This bulk of helpful data is difficult to analyse and also a time consuming task. So,an intelligent text mining system that can automatically analyse and categorise such vast user generated data is needed. Due to the noisiness in data, it is difficult to design such a processing technique because of spelling mistakes, grammatical errorsand improper punctuation. Automatic opinion extraction is a useful technique to monitor consumers' feedback regarding any particular productsin terms of positive or negative.The management of customer relations can use these feedbacks to improve the products and services and ultimately can make the clients happy. Support Vector Machine (SVM) is one of the most famous and useful supervised machine learning technique used for sentiment classification and opinion extraction. Many extensions and modifications of this algorithm are available today. The purpose of this research is to improve the SVM accuracy through grid search technique for sentiment classificationof textual data.


URI : https://vspace.vu.edu.pk/details.aspx?id=124

Citation: Ahmad, M(2017), OPTIMIZATION OF SVM FOR SENTIMENT ANALYSIS, Virtual University of Pakistan (Lahore, Pakistan).

Version : Final Version

Terms of Use :

Detailed Terms :

Journal :

Files in this item

Name Size Format
Fall 2017_CS720_MS140400083.pdf 948kb pdf


Copyright 2016 © Virtual University of Pakistan