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An Ontology-Based Text-Mining Method develop intelligent information system using cluster based approach

机译:基于本体的文本挖掘方法使用基于集群的方法开发智能信息系统

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Text clustering is an important task. Generally, text document clustering methods attempt to segregate the documents into groups where each group represents some topic if the topics are same then they are belonging in the same group if the topics are different then new group can be created with the help of cluster and that different topic store in new group. In this paper has present an clustering on ontology based text mining for grouping paper or proposals and assigning that grouped proposal to reviewers systematically. It facilitates text-mining and some text extraction techniques to cluster approach based on their similarities and then to assign them to reviewer and obtain text summarization. A principled approach is proposed to develop an intelligent information system by analyzing the unstructured repair verbatim data. Construct the fault diagnosis ontology for find out the fault so that extract the irrelevant information. The three text mining technique can be used for creating intelligent information system. The proposed method is that analysis of text summarization and plagiarism analysis and find out the efficiency i.e. time complexity and increase the performance of system using cluster based approach.
机译:文本群集是一项重要任务。通常,文本文档群集方法尝试将文档分成分组,其中每个组代表某些主题如果主题相同,则它们属于同一组,如果主题是不同的,则可以在群集中创建新组新组中的不同主题商店。本文为基于本体的文本挖掘提供了对分组文件或提案的集群,并将其分配给审阅者系统地分配。它促进了文本挖掘和一些文本提取技术,以基于其相似之处的聚类方法,然后将它们分配给审阅者并获得文本摘要。建议通过分析非结构化修复逐字数据来开发智能信息系统的原则方法。构建故障诊断本体,以找出故障,从而提取无关信息。三种文本挖掘技术可用于创建智能信息系统。该方法是分析文本摘要和抄袭分析,并找出效率即时间复杂性,并使用基于集群的方法提高系统的性能。

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