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Text Document Clustering with Ontology Applying Modify Concept Weighting

机译:文本文档群集与本体应用修改概念加权

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With the increasing amount of information, researchers in digital communities have witnessed the tremendous growth of publications. The overwhelming amount of information still makes it a time-consuming task. There are many of computer science and medical subject related documents cited on the Internet. Ontologies currently are hot topics in the area of Semantic Web. Ontologies can also help in addressing the problem of searching related entities, including research publications. The purpose of the system is to cluster the text documents based upon the ontology. The system is applying the modified concept weighting and become the extended version of the work that has been done before [8]. After the time passed the testing amount of data becomes lager and the challenges is the time complexity. To overcome this issue the system used the scoring method at the concept weighting stages to manage the time complexity. The experiments reveal that even the testing documents increased; the system may actually be able to produce useful result for text document clustering.
机译:随着信息量越来越多,数字社区的研究人员目睹了出版物的巨大增长。压倒性的信息仍然使它成为耗时的任务。互联网上有许多计算机科学和医学主题相关文件。本体目前是语义网络区域的热门话题。本体也可以帮助解决搜索相关实体的问题,包括研究出版物。该系统的目的是基于本体进行群集文本文档。该系统正在应用修改后的概念加权,并成为在[8]之前完成的工作的扩展版本。经过通过后,数据测试量变为储存,挑战是时间复杂性。为了克服这个问题,系统在概念加权阶段使用评分方法来管理时间复杂性。实验表明,即使是测试文件也增加;系统实际上可以能够为文本文档聚类产生有用的结果。

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