MultiSOM:一种精确分析和挖掘复杂数据的多视图神经模型

Jean-Charles Lamirel, S. Al Shehabi
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引用次数: 9

摘要

在信息分析的过程中,就像在专利分析领域一样,研究主题的复杂性和要回答的问题的准确性往往会导致分析人员将他的推理划分为观点。大多数经典的信息分析工具只能以全局的方式管理所研究领域的分析。本文考虑的信息分析工具是MultiSOM工具,其核心模型是对经典Kohonen SOM神经模型的重要扩展。基于神经网络的MultiSOM工具通过其多地图显示和地图间通信过程,将视点和动态的概念引入信息分析。分析人员可以利用映射之间的动态信息交换,以便在对同一数据执行的几个不同分析之间执行协作演绎。本文证明了与专利领域的全局分析相比,以观点为导向的分析的效率。质量评价既考虑客观质量标准,又考虑主观质量标准
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MultiSOM: A Multiview Neural Model for Accurately Analyzing and Mining Complex Data
In the procedure of information analysis, like in the domain of patent analysis, the complexity of the studied topics and the accuracy of the question to be answered may often lead the analyst to partition his reasoning into viewpoints. Most of the classical information analysis tools can only manage an analysis of the studied domain in a global way. The information analysis tool is considered in this paper is the MultiSOM tool, whose core model represents a significant extension of the classical Kohonen SOM neural model. The MultiSOM neural-based tool introduces the concepts of viewpoints and dynamics into the information analysis with its multi-maps displays and its inter-map communication process. The dynamic information exchange between maps can be exploited by an analyst in order to perform cooperative deduction between several different analyzes that have been performed on the same data. This paper demonstrates the efficiency of a viewpoint-oriented analysis as compared to a global analysis in the domain of patents. Both objective and subjective quality criteria are taken into account for quality evaluation
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