Analysis of Knowledge Management in Industrial Sectors by Means of Neural Models

被引：2
|
作者：
Herrero, Alvaro [1 ]
Corchado, Emilio [2 ]
Saiz-Barcena, Lourdes [1 ]
Manzanedo, Miguel A. [1 ]
机构：
[1] Univ Burgos, Dept Civil Engn, Ave Cantabria S-N, Burgos 09006, Spain
[2] Univ Salamanca, Dept Informat & Automat, E-37008 Salamanca, Spain
来源：
10TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS | 2015年 / 368卷
关键词：
Knowledge management; Unsupervised neural networks; Exploratory projection pursuit;
D O I：
10.1007/978-3-319-19719-7_6
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
It is required for an organization, before successfully applying a Knowledge Management (KM) methodology, to develop and implement a knowledge infrastructure, consisting of people, organizational and technological systems. Up to now, few approaches have been proposed for such technological systems supporting KM in organizations. Present paper advances previous work by proposing neural projection models for the analysis of the KM status of companies from two different industrial sectors. Exploratory methods are applied to real-life case studies to know and understand the structure of KM data. Subsequently, the application of such models generates meaningful conclusions that allow experts to diagnose KM from two different points of view: companies on the one hand and industrial sectors on the other hand.
引用
收藏
页码：65 / 75
页数：11
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