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Effective pattern discovery for taxt mining using PTM and PDM

机译:使用PTM和PDM进行出租车开采的有效模式发现

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Text mining is the process of discovery of interesting knowledge in text documents, many data mining techniques have been proposed for mining useful patterns in text documents. It is challenging issue to accurate knowledge in [1] text documents to help uses to find what they want. In existing information system they provided many term based methods to solve this challenge. As we know the term-based methods suffers from the problem of polysemy and synonymy. The polysemy means the word has multiple meanings and synonymy is multiple words having the same meaning. In propose to use pattern or phrase based approach so it will perform better than the term based approach. In the proposed approach can improve the accuracy of evaluating term weights because discovered patterns or most specific than whole documents. In this paper we focus on innovative and effective pattern discovery techniques as well as architecture of proposed system. Then we will study how pattern taxonomy model and deploying model is useful for the effective pattern discovery for Text Mining.
机译:文本挖掘是在文本文档中发现有趣知识的过程,已经提出了许多数据挖掘技术来挖掘文本文档中的有用模式。在[1]文本文档中准确的知识来帮助用户查找所需内容是具有挑战性的问题。在现有的信息系统中,他们提供了许多基于术语的方法来解决这一难题。众所周知,基于术语的方法存在多义和同义的问题。多义性意味着单词具有多种含义,而同义词是具有相同含义的多个单词。在提议使用基于模式或短语的方法时,它将比基于术语的方法更好地执行。在提议的方法中,由于发现的模式或比整个文档最具体的模式,因此可以提高评估术语权重的准确性。在本文中,我们专注于创新和有效的模式发现技术以及所提出系统的体系结构。然后,我们将研究模式分类法模型和部署模型对于文本挖掘的有效模式发现如何有用。

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