数据分析使用数据挖掘技术收集和分析非结构化和半结构化的信息

S. Papavlasopoulos
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引用次数: 0

摘要

在本研究中,一个理论模型的组合,从一个调查问卷的所有个别问题进行了研究。为了实现这一目标,使用了一个良好的Elman神经网络来制定问卷问题之间的权重关系,该问卷是为“加强中小企业之间合作和国际化的创新服务”(I.S.C.I.)项目制作的,该项目以中小型企业(意大利普利亚地区和希腊爱奥尼亚群岛)的农业食品工业的国际化过程为目标。本研究的目的是利用数据挖掘技术对上述问卷进行评估,其中专家的心理处理与Elman神经网络相连接。为此,使用了适当的问卷调查,以便根据其绩效将中小企业分为三(3)类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data analysis for gathering and analysis of no structured and semi-structured information using data mining technique
In this study, a theoretical model for the combination of all individual questions from a questionnaire is investigated. For this implementation, a well-fitted Elman neural network is used in order to formulate the weighting relations between questions of the questionnaire which is produced for the project “Innovative Services to Strengthen Cooperation and Internationalization between SMEs” (I.S.C.I.) which has as objective the internationalization processes of the agro food industry of the Small and Medium-sized Enterprises (SMEs) (in Apulia Region, Italy, and in Ionian Islands, Greece). The aim of this study is the evaluation of the above questionnaire using a data mining technique in which the mental processing of an expert is linking with the Elman Neural Network. For this reason a proper questionnaire was used in order to classify the SMEs into three (3) classes according to their performance.
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