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首页> 外文期刊>The international arab journal of information technology >Analysis and Performance Evaluation of Cosine Neighbourhood Recommender System
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Analysis and Performance Evaluation of Cosine Neighbourhood Recommender System

机译：余弦邻域推荐系统分析与性能评估

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摘要

Growth of technology and innovation leads to large and complex data which is coined as Bigdata. As the quantity of information increases, it becomes more difficult to store and process data. The greater problem is finding right data from these enormous data. These data are processed to extract the required data and recommend high quality data to the user. Recommender system analyses user preference to recommend items to user. Problem arises when Bigdata is to be processed for Recommender system. Several technologies are available with which big data can be processed and analyzed. Hadoop is a framework which supports manipulation of large and varied data. In this paper, a novel approach Cosine Neighbourhood Similarity measure is proposed to calculate rating for items and to recommend items to user and the performance of the recommender system is evaluated under dfferent evaluator which shows the proposed Similarity measure is more accurate and reliable.
机译：技术和创新的发展导致了大而复杂的数据，即大数据。随着信息量的增加，存储和处理数据变得更加困难。更大的问题是从这些巨大的数据中查找正确的数据。处理这些数据以提取所需的数据并向用户推荐高质量的数据。推荐系统分析用户偏好以向用户推荐项目。要为推荐系统处理Bigdata时会出现问题。可以使用多种技术来处理和分析大数据。 Hadoop是一个支持处理大量不同数据的框架。本文提出了一种新的余弦邻域相似度度量方法，用于计算项目的评分并向用户推荐项目，并在不同的评估器下对推荐系统的性能进行了评估，结果表明所提出的相似度度量更加准确可靠。

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