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  <dc:date>2008-07-20T23:40:57+02:00</dc:date>

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<item rdf:about="http://www.bibsonomy.org/uri/bibtex/22b8ad9673ff3405744ba10e678aebfaf/renew">
    <title>RRSS - Rating Reviews Support System Purpose Built for Movies Recommendation</title>
    <description>SpringerLink - Book Chapter</description><link>http://www.bibsonomy.org/bibtex/22b8ad9673ff3405744ba10e678aebfaf/renew</link>
    <dc:creator>renew</dc:creator>
    <dc:date>2008-02-22T21:29:26+01:00</dc:date>
    <dc:subject>movie recommendation system </dc:subject>
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  <a href="http://www.bibsonomy.org/bibtex/22b8ad9673ff3405744ba10e678aebfaf/renew">RRSS - Rating Reviews Support System Purpose Built for Movies Recommendation</a>
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  <span style="color:#555555;"> 
    Grzegorz <a href="http://www.bibsonomy.org/author/Dziczkowski">Dziczkowski</a>         	     	 
        	  and Katarzyna <a href="http://www.bibsonomy.org/author/Wegrzyn-Wolska">Wegrzyn-Wolska</a>         	     	 
        	 </span> 
  <em>Advances in Intelligent Web Mastering</em>
    87--93
  (2007)
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        <a href="http://www.bibsonomy.org/user/renew/movie">movie</a>
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        <a href="http://www.bibsonomy.org/user/renew/system">system</a>
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          by <a href="http://www.bibsonomy.org/user/renew">renew</a> 
        
        
        on 2008-02-22 21:29:26 </span></div>
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        <swrc:booktitle>Advances in Intelligent Web Mastering</swrc:booktitle><swrc:pages>87--93</swrc:pages><swrc:title>RRSS - Rating Reviews Support System Purpose Built for Movies Recommendation</swrc:title><swrc:year>2007</swrc:year><swrc:keywords>movie recommendation system </swrc:keywords><swrc:date>2008-02-22 21:29:26.0</swrc:date><swrc: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 andretrieves texts supposed to be movie reviews from the Internet. Subsequently the system carries out an evaluation and ratingof the movie reviews. Finally, the system automatically associates a digital assessment with each review. The goal of thesystem is to give the score of reviews associated with the user who wrote them. All of this data is the input to the cognitiveengine. Data from our base allows the making of correspondences, which are required for cognitive algorithms to improve, advancedrecommending functionalities for e-business and e-purchase websites. In this paper we will describe the different methodson automatically identifying opinions using natural language knowledge and techniques of classification.</swrc:abstract><swrc:author>
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