An Autonomous System Designed for Automatic Detection and Rating of Film Reviews

This paper describes the functions of a system designed for the assessment of movie reviews. Such a system enables the automatic collection, evaluation and rating of film criticspsila opinions of movies. First the system searches and retrieves probable movie reviews from the Internet, especially those expressed by prolific reviewers. Subsequently the system carries out an evaluation and rating of those movie reviews. Finally the system automatically associates a numerical mark to each review, this is the objective of the system. This data constitutes the input to the cognitive engine. Our system uses three different methods for classifying opinions in criticspsila reviews. We introduce two new methods based on linguistic knowledge. Results are then compared with the overall statistical method using Bayes classifier. The last step is to combine the results obtained in order to make the final assessment as accurately as possible.

[1]  Dziczkowski Grzegorz,et al.  Graph based system purpose: built for automatic retrieval and extraction of the electronics data , 2007 .

[2]  H. Kamp,et al.  Evénements, représentations discursives et référence temporelle , 1981 .

[3]  M. Gross The Construction of Local Grammars , 1997 .

[4]  Janyce Wiebe,et al.  Learning Subjective Language , 2004, CL.

[5]  Katarzyna Wegrzyn-Wolska,et al.  Tool of the Intelligence Economic: Recognition Function of Reviews Critics - Extraction and Linguistic Analysis of Sentiments , 2008, ICSOFT.

[6]  Michael L. Littman,et al.  Measuring praise and criticism: Inference of semantic orientation from association , 2003, TOIS.

[7]  Loren Terveen,et al.  Beyond Recommender Systems: Helping People Help Each Other , 2001 .

[8]  Brian Eriksson,et al.  SENTIMENT CLASSIFICATION OF MOVIE REVIEWS USING LINGUISTIC PARSING , 2006 .

[9]  David M. Pennock,et al.  Mining the peanut gallery: opinion extraction and semantic classification of product reviews , 2003, WWW '03.

[10]  Katarzyna Wegrzyn-Wolska,et al.  RRSS - Rating Reviews Support System Purpose Built for Movies Recommendation , 2007, AWIC.

[11]  Alistair Kennedy,et al.  SENTIMENT CLASSIFICATION of MOVIE REVIEWS USING CONTEXTUAL VALENCE SHIFTERS , 2006, Comput. Intell..

[12]  Yong Wang,et al.  Classification of Web documents using a naive Bayes method , 2003, Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence.

[13]  Bo Pang,et al.  A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts , 2004, ACL.

[14]  H. Alshawi,et al.  The Core Language Engine , 1994 .

[15]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[16]  Sébastien Paumier De la reconnaissance de formes linguistiques à l'analyse syntaxique. (From Pattern Matching in Text to Syntactic Parsing) , 2003 .

[17]  Maria Teresa Pazienza,et al.  Information Extraction A Multidisciplinary Approach to an Emerging Information Technology , 1997, Lecture Notes in Computer Science.