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The design and implementation of distributed mobile points of interest(POI) based on Mahout

机译:基于Mahout的分布式移动兴趣点(POI)的设计与实现。

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The paper is based on the machine learning development status and in-depth analysis and comparison of Mahout's machine learning algorithm, summarizes the principles of different Mahout's recommendation algorithm, characteristics, implementation method and function. Then the paper takes the characteristics of user recommendation system into consideration, design the user recommendation system, analysis the characteristics and issues of design and make further improvement; then make use of Mahout and Hadoop to accomplish the user recommendation system, which can dynamically capture user preferences, provide the user with recommendation when the user browses the web page. Finally, through practice, Hadoop and Mahout can meet the demand of massive data processing, and achieve a highly performance system by making use of the data re-processing method.
机译:本文基于机器学习的发展现状,并对Mahout的机器学习算法进行了深入的分析和比较,总结了Mahout的各种推荐算法的原理,特点,实现方法和功能。然后考虑了用户推荐系统的特点,设计了用户推荐系统,分析了设计的特点和问题,并进行了进一步的改进。然后利用Mahout和Hadoop来完成用户推荐系统,该系统可以动态捕获用户的偏好,并在用户浏览网页时为用户提供推荐。最后,通过实践,Hadoop和Mahout可以满足海量数据处理的需求,并通过使用数据重新处理方法来实现高性能的系统。

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