Main Reference PaperMovie Rating and Review Summarization in Mobile Environment, IEEE Transactions on Parallel and Distributed Systems, May 2012.
  • In this project Sentiment classification is utilized for classifying the sentiment of movie reviews and rating information is based on sentiment classification result. SVM method is used for sentiment classification. It classifies the movie reviews into positive or negative polarity. This polarity is further used for rating the movie.

+ Description
  • In this project Sentiment classification is utilized for classifying the sentiment of movie reviews and rating information is based on sentiment classification result. SVM method is used for sentiment classification. It classifies the movie reviews into positive or negative polarity. This polarity is further used for rating the movie.

  • It aims to develop a movie rating and review summarization system in a mobile environment.

  • It proposes a novel approach on LSA for identifying the product features.

  • It provides an LSA-based filtering mechanism to allow the users to choose the features .

+ Aim & Objectives
  • It aims to develop a movie rating and review summarization system in a mobile environment.

  • It proposes a novel approach on LSA for identifying the product features.

  • It provides an LSA-based filtering mechanism to allow the users to choose the features .

  • The new contribution of this project is to propose a novel approach based on LSA to identify related product-feature terms. Basically,LSA is a premise and technique to explore relationships between a set of documents and the terms they contain by producing a set of concepts associated to the documents and terms.

+ Contribution
  • The new contribution of this project is to propose a novel approach based on LSA to identify related product-feature terms. Basically,LSA is a premise and technique to explore relationships between a set of documents and the terms they contain by producing a set of concepts associated to the documents and terms.

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, J2EE

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, J2EE

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.