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Rating based mechanism to contrast abnormal posts on movies reviews using MapReduce paradigm

机译:基于评级的机制使用MapReduce范例对比电影评论中的异常帖子

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BigData contains large amount of unstructured data in the form of movie data, facebook data, and industry data and so on. There are number of posts are posted on Twitter about movies by different users. Out of these posts some of posts may be inappropriate. These posts contain negative comments as well as positive comments about movies. It is difficult to distinguish large number of positive and negative posts. To overcome this kind of problem we proposed a rating based mechanism that distinguishes abnormal posts with the help of users rating. If rating is positive then post is normal otherwise it is abnormal. To implement proposed mechanism we used hadoop platform and MapReduce paradigm.
机译:BigData以电影数据,facebook数据和行业数据等形式包含大量非结构化数据。 Twitter上有许多关于不同用户的电影的帖子。在这些帖子中,有些帖子可能是不合适的。这些帖子包含有关电影的负面评论和正面评论。很难区分大量的正面和负面职位。为了克服这种问题,我们提出了一种基于评分的机制,该机制可以在用户评分的帮助下区分异常帖子。如果评分为正,则发布正常,否则为异常。为了实现所提出的机制,我们使用了hadoop平台和MapReduce范例。

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