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A survey on methodologies used for semantic document clustering

机译：语义文档聚类方法的调查

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摘要

Document clustering is a traditional technique, and is used in multiple fields like data mining, information retrieval, knowledge discovery from data, pattern recognition etc. Large volumes of textual data being created in the modern world have resulted in the rise in importance of document clustering techniques. Although various document-clustering techniques have been studied in recent years, clustering quality still remains an area of concern. Particularly, majority of the present document clustering methods do not account for the semantic relationships and as a result give unsatisfactory clustering results. Semantic relationships consider the context of the usage of the term and do not solely rely on its isolated meaning. In the recent years, a lot of effort has gone into applying semantics to document clustering. This paper presents a survey of various research papers that have been studied and highlights the merits and demerits of each clustering algorithm. This will give a direction to future research in a more focused manner.
机译：文档聚类是一种传统技术，用于多个领域，例如数据挖掘，信息检索，数据知识发现，模式识别等。在现代世界中创建的大量文本数据导致文档聚类的重要性日益提高。技术。尽管近年来已经研究了各种文档聚类技术，但是聚类质量仍然是一个值得关注的领域。特别地，大多数本文档聚类方法没有考虑语义关系，结果给出了不令人满意的聚类结果。语义关系考虑了该术语使用的上下文，并不仅仅依赖于其孤立的含义。近年来，在将语义应用于文档聚类方面付出了很多努力。本文介绍了已研究的各种研究论文，并重点介绍了每种聚类算法的优缺点。这将为将来的研究提供更集中的方向。

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