CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Mining Movie Intention using Bayes and Maximum Entropy Classifiers

Published on January 2018 by Varsha D. Jadhav, Sachin N. Deshmukh
journal_cover_thumbnail

International Conference on Cognitive Knowledge Engineering
Foundation of Computer Science USA
ICKE2016 - Number 2
January 2018
Authors: Varsha D. Jadhav, Sachin N. Deshmukh
3712ba78-fade-40ab-bc33-e67e49e837a7

Varsha D. Jadhav, Sachin N. Deshmukh . Mining Movie Intention using Bayes and Maximum Entropy Classifiers. International Conference on Cognitive Knowledge Engineering. ICKE2016, 2 (January 2018), 8-19.

@article{
author = { Varsha D. Jadhav, Sachin N. Deshmukh },
title = { Mining Movie Intention using Bayes and Maximum Entropy Classifiers },
journal = { International Conference on Cognitive Knowledge Engineering },
issue_date = { January 2018 },
volume = { ICKE2016 },
number = { 2 },
month = { January },
year = { 2018 },
issn = 0975-8887,
pages = { 8-19 },
numpages = 12,
url = { /proceedings/icke2016/number2/28951-6065/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Cognitive Knowledge Engineering
%A Varsha D. Jadhav
%A Sachin N. Deshmukh
%T Mining Movie Intention using Bayes and Maximum Entropy Classifiers
%J International Conference on Cognitive Knowledge Engineering
%@ 0975-8887
%V ICKE2016
%N 2
%P 8-19
%D 2018
%I International Journal of Computer Applications
Abstract

Sentiment analysis is becoming one of the most thoughtful research areas for prediction and classification. This paper analyzes and predicts the result for movie reviews. Machine learning techniques Bayes and Maximum entropy for classifying text messages. Movie comments from twitter are retrieved. The two classifiers are analyzed for Hindi movies 'Sultan' and 'Madaari. ' Tweets before and after the release of the movie are retrieved. Accuracy is evaluated to compare the Bayes and Maximum entropy methods. R technology is used for the movie review analysis.

References
  1. Minqing Hu and Bing Liu, "Mining and Summarizing Customer Reviews," DD'04, August 22–25, 2004, Seattle, Washington, USA.
  2. Varsha D Jadhav, S. N. Deshmukh, "Twitter Intention Classification Using Bayes Approach for Cricket Test Match Played Between India and South Africa 2015," Proceeding of International Conference on Internet of Things, Next Generation Network and Cloud Computing 2016. ISSN: 0975 – 8887,
  3. Kamal Nigam,John Lafferty, Andrew McCallum, "Using maximum entropy for text classification," In IJCAI-99 Workshop on Machine Learning for Information Filtering.
  4. Kuat Yessenov, Sasa Misailovic, Sentiment Analysis of Movie Review Comments," 6. 863 Spring 2009 final project, May 17, 2009.
  5. Changlin Ma, Meng Wang, Xuewen Chen, "Topic and Sentiment Unification Maximum Entropy Model for Online Review Analysis," WWW 2015 Companion, May 18–22, 2015, Florence, Italy. ACM 978-1-4503-3473-0/15/05.
  6. Oaindrila Das, Rakesh Chandra Balabantaray, "Sentiment Analysis of Movie Reviews using POS tags and Term Frequencies," International Journal of Computer Applications (0975 – 8887) Volume 96– No. 25, June 2014.
  7. Borislav Kapukaranov, Preslav Nakov, "Fine-Grained Sentiment Analysis for Movie Reviews in Bulgarian," Proceedings of Recent Advances in Natural Language Processing, pages 266–274,Hissar, Bulgaria, Sep 7–9 2015.
  8. Cort J. Willmott, Kenji Matsuura, "Advantages of the mean absolute error (MAE) over the root mean square error RMSE) in assessing average model Performance, Climate Research, Vol. 30: 79–82.
  9. http://timesofindia. indiatimes. com, Hindi movie reviews.
Index Terms

Computer Science
Information Sciences

Keywords

Bayes Maximum Entropy Polarity Emotions Mean Absolute Error