Abstract
This paper describes the part of a recommendation system designed for the recognition of film reviews (RRSS). Such a system allows the automatic collection, evaluation and rating of reviews and opinions of the movies. First the system searches and retrieves texts supposed to be movie reviews from the Internet. Subsequently the system carries out an evaluation and rating of the movie reviews. Finally, the system automatically associates a digital assessment with each review. The goal of the system is to give the score of reviews associated with the user who wrote them. All of this data is the input to the cognitive engine. Data from our base allows the making of correspondences, which are required for cognitive algorithms to improve, advanced recommending functionalities for e-business and e-purchase websites. In this paper we will describe the different methods on automatically identifying opinions using natural language knowledge and techniques of classification.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Altai, H.: The core language Engine. ACL-MIT Press Series in Natural language Processing. MIT Press, Cambridge (1992)
Cover, T.M.: Elements of Information Theory. John Wiley, Chichester (1991)
Dave, K., Lawrance, S., Pennock, D.M.: Mining the Peanut Gallery: Opinion Extraction with HMM Structures Learned by Stochastic Optimization. In: AAAI-2000 (2003)
Dziczkowski, G., Wegrzyn-Wolska, K.: Graph based system purpose - built for automatic retrieval and extraction of the electronics data. To appear in proceeding of Euro-IMSA, Mars (2007)
Gross, M.: The construction of local grammars. In: Finite-State Language Processing, pp. 329–354. MIT Press, Cambridge (1997)
Kamp, H.: Evenements representations discursives et reference temporelle. Langages 64, 34–64 (1981)
Pang, B., Lee, L.: A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts. In: ACL-04 (2004)
Pazienza, M.T. (ed.): Information extraction – A multidisciplinary approach to an emerging information technology. LNCS, vol. 1299. Springer, Heidelberg (1997)
Paumier, S.: De La reconnaissance de formes linquistique a l’analyse syntaxique. These, Marne-la-Valee (2003)
Riloff, E., Wiebe, J., Philips, W.: Exploiting Subjectivity Classification to Improve Information Extraction
Sowa, J.: Conceptual Structures. Information processing in Mind and Machine. Wesley Publishing, Reading (1984)
Tarveen, L., Hill, W.: Beyond recommender systems: helping people help each other. In: Caroll, J. (ed.) HCI in the millennium, vol. 2001, pp. 1–21. Addison-Wesley, Reading (2001)
Turney, P., Littman, M.: Measuring Praise and Criticism: Inference of Semantic Orientation from Association. ACM Transaction on Information Systems (TOIS) 21(4), 315–346 (2003)
Wang, Y., Hodges, J., Tang, B.: Classification of Web Documents using a Naive Bayes Method, pp. 560–564. IEEE Computer Society Press, Los Alamitos (2003)
Wiebe, J., et al.: Learning Subjective Language. Computational Linguistics 30(3), 277–308 (2004)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Dziczkowski, G., Wegrzyn-Wolska, K. (2007). RRSS - Rating Reviews Support System Purpose Built for Movies Recommendation. In: Wegrzyn-Wolska, K.M., Szczepaniak, P.S. (eds) Advances in Intelligent Web Mastering. Advances in Soft Computing, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72575-6_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-72575-6_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72574-9
Online ISBN: 978-3-540-72575-6
eBook Packages: EngineeringEngineering (R0)