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The Big Data Mining Approach for Finding top rated URL

机译:大数据挖掘方法,用于查找评分最高的URL

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Finding out the widely used URL’s from online shopping sites for any particular category is a difficult task as there are many heterogeneous and multi-dimensional data set which depends on various factors. Traditional data mining methods are limited to homogenous data source, so they fail to sufficiently consider the characteristics of heterogeneous data. This paper presents a consistent Big Data mining search which performs analytics on text data to find the top rated URL’s. Though many heuristic search methods are available, our proposed method solves the problem of searching compared with traditional methods in data mining. The sample results are obtained in optimal time and are compared with other methods which is effective and efficient.
机译:从在线购物网站中找到任何特定类别的广泛使用的URL是一项艰巨的任务,因为存在许多异构数据和多维数据集,这些数据集取决于各种因素。传统的数据挖掘方法仅限于同质数据源,因此它们无法充分考虑异质数据的特性。本文介绍了一致的大数据挖掘搜索,该搜索对文本数据进行分析以找到评分最高的URL。尽管有许多启发式搜索方法可用,但与数据挖掘中的传统方法相比,我们提出的方法解决了搜索问题。在最佳时间内获得样品结果,并将其与其他有效且高效的方法进行比较。

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