基于Pig和Hadoop的电影分析推荐系统

Arushi Jain, Vishal Bhatnagar
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引用次数: 30

摘要

自18世纪后期电影问世以来,电影一直是人们娱乐的重要来源。电影这个词是非常广泛的,它的定义包含了语言和类型,如戏剧、喜剧、科幻和动作。多年来关于电影的数据非常庞大,要对其进行分析,需要突破传统的分析技术,采用大数据分析。在本文中,作者对电影数据集进行了分析,并针对各种查询进行了分析,以从数据集中发现有效的推荐系统和即将上映的电影的评级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Movie Analytics for Effective Recommendation System using Pig with Hadoop
Movies have been a great source of entertainment for the people ever since their inception in the late 18th century. The term movie is very broad and its definition contains language and genres such as drama, comedy, science fiction and action. The data about movies over the years is very vast and to analyze it, there is a need to break away from the traditional analytics techniques and adopt big data analytics. In this paper the authors have taken the data set on movies and analyzed it against various queries to uncover real nuggets from the dataset for effective recommendation system and ratings for the upcoming movies.
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