Implementation of pattern discovery to retrieve relevant document using text mining

Shiva Gupta, B. P. Vasgi
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引用次数: 4

Abstract

Many data mining techniques are used to extract the patterns from the text documents. But the challenge is using those updated patterns is still a open research issue. Most of the text mining methods generally uses the term based approaches. The main problems faced by the term based approaches is of polysemy and synonymy. This paper focuses on the implementation of an particular discovery way to discover the pattern as well as use them to retrieve the relevant document. Two important process are used i.e pattern deploying and pattern evolving is included as the pattern discovery techniques. These techniques finds to be helpful in improving the effectiveness of the discovered patterns. These discovered patterns can be used in searching the relevant and important information for text mining. To improve the effectiveness of using and updating discovered patterns according to users view, experiments on RCV1 data collection achieves user required data from a large document by removing noisy pattern by pattern evolving.
使用文本挖掘实现模式发现以检索相关文档
许多数据挖掘技术用于从文本文档中提取模式。但挑战在于使用这些更新的模式仍然是一个开放的研究问题。大多数文本挖掘方法通常使用基于术语的方法。基于术语的方法面临的主要问题是一词多义和同义词问题。本文着重于实现一种特殊的发现方式来发现模式并使用它们来检索相关文档。使用了两个重要的过程,即模式部署和模式演化,作为模式发现技术。这些技术有助于提高所发现模式的有效性。这些发现的模式可用于搜索文本挖掘的相关和重要信息。为了提高根据用户视图使用和更新发现模式的有效性,RCV1数据采集实验通过逐模式演化去除噪声模式,从大型文档中获得用户需要的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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