基于模糊可变形原型的动态web库信息过滤推理

F. P. Romero, J. A. Olivas, P. J. Garcés
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引用次数: 3

摘要

提出了一种基于模糊可变形原型的动态web库文档过滤模型。该模型基于文档的模糊层次分类。它定义了一个简单的过程来处理传入的文档和一个有效的方法来更新它们的结构。该过程将文档聚类的模糊原型与文档内容的可用信息进行比较。它利用基于概念的过滤标准和基于类别的过滤技术向用户提供文档的智能结构。由于过滤是一个动态过程,知识库可以更新现有文档的层次结构。采用基于模糊可变形原型的推理方法,可以在新文档进入知识库时方便有效地更新聚类层次结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inference based on Fuzzy Deformable Prototypes for information filtering in dynamic web repositories
In this paper, a novel document filtering model in dynamic web repositories based on fuzzy deformable prototypes is presented. This model is based on fuzzy hierarchical categorization of documents. It defines an easy process to deal with the incoming documents and an efficient method to update their structure. The process is performed comparing the fuzzy prototypes of document cluster with the available information about documents contents. It exploits conceptual-based filtering criteria and category-based filtering techniques to deliver to the user an intelligent structure of the documents. Since filtering is a dynamic process, the knowledge base can update the hierarchy of existing documents. The clusters hierarchy can be easily and efficiently updated when new documents income on the repository by means of an inference method which is based on fuzzy deformable prototypes.
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