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Movies Recommenders Systems: Automation of the Information and Evaluation Phases in a Multi-criteria Decision-Making Process

机译:电影推荐者系统:多标准决策过程中信息和评估阶段的自动化

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The authors' interest is focused on advanced recommending functionalities proposed by more and more Internet websites w.r.t. the selection of movies, e-business sites, or any e-purchases. These functionalities often rely on the Internet users' opinions and evaluations. A «movie-recommender» application is presented. Recommender websites generally propose an aggregation of the user's evaluations critics according to different relevant criteria w.r.t. the application. The authors propose an Information Processing System (IPS) to collect, process and manage as automatically as possible these opinions or critics to support this multi criteria evaluation for recommendation. The RS (Recommender System) firstly proposes information extraction techniques in order to classify the available users' critics w.r.t. the criteria implied in the evaluation process and to automatically associate numerical scores to these critics. Then multicriteria techniques are introduced to numerically evaluate, compare and rank the competing movies the critics are reported to. Finally the RS is presented as an interactive Decision-Making Support System (DMSS) relying on a sensibility analysis of the movies ranking. A particular attention is paid to the automation of the information phase in the decision-making process: movie comments cartography according to users' evaluation criteria and attribution of a partial score to each critic considered as the expression of a value judgment in natural language.
机译:作者的兴趣专注于越来越多的互联网网站提出的高级推荐功能W.R.T.电影,电子商务网站或任何电子购买的选择。这些功能往往依赖互联网用户的意见和评估。 «电影推荐人»应用程序。推荐人网站通常根据不同的相关标准提出用户的评估批评的聚合。应用程序。作者提出了一种信息处理系统(IP),以自动收集,处理和管理,尽可能自动地支持这些意见或批评者以支持这种多标准评估。 RS(推荐系统)首先提出信息提取技术,以便将可用用户的批评者归类为W.R.T.评估过程中暗示的标准,并自动将数值分数与这些批评者联系起来。然后将多轨道技术引入数值评估,比较和排列竞争和排名批评批评者。最后,RS被呈现为依赖于电影排名的敏感性分析的互动决策支持系统(DMS)。特别注意决策过程中信息阶段的自动化:电影评论制图根据用户的评价标准和归因于每个评论家被视为自然语言中价值判断的表达的每个评论家。

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