| 基于N-IKOS自动分类的实证研究 |
| |
| 引用本文： | 王兴兰,宋文.基于N-IKOS自动分类的实证研究[J].图书情报工作,2014,58(24):106-112. |
| |
| 作者姓名： | 王兴兰 宋文 |
| |
| 作者单位： | 1. 重庆医科大学图书馆;
2. 中国科学院文献情报中心 |
| |
| 摘 要： | 指出大数据时代的到来使自动分类再次受到人们的关注.总结现有的自动分类方法,介绍中国科学院文献情报中心的KOS引擎项目中的集成知识组织体系.在此基础上,改进BP神经网络算法,提出N-IKOS自动分类模型.最后,通过实验检验基于N-IKOS分类的准确性,通过基于BP神经网络的分类实验、基于KOS引擎的分类实验和基于N-IKOS的分类实验比较新模型在自动分类中的优劣.实验结果表明:该研究改进了原有的KOS引擎分类,可为自动分类领域提供新的思路.
|
| 关 键 词： | 自动分类 知识组织体系 机器学习 BP神经网络 |
| 收稿时间： | 2014-10-08 |
| 修稿时间： | 2014-12-05 |
The Empirical Study on Automatic Classification Based on N-IKOS |
| |
| Wang Xinglan,Song Wen.The Empirical Study on Automatic Classification Based on N-IKOS[J].Library and Information Service,2014,58(24):106-112. |
| |
| Authors: | Wang Xinglan Song Wen |
| |
| Institution: | 1. library of Chongqing Medical University, Chongqing 400016;
2. National Science Library of Chinese Academy of Sciences, Beijing 100190 |
| |
| Abstract: | Automatic classification is taken attention again with the coming of big data.The paper summaries the methods of automatic classification,and introduces the integrated knowledge organization system in KOS engine project of National Science Library.Then,it improves the BP neural network,and raises a pattern of N-IKOS automatic classification.In the end,the paper tests the accuracy of N-IKOS automatic classification by experiment,and compares the merits and drawbacks of the new model with the experiments of automatic classification based on BP neural network KOS engine and N-IKOS.It improves the category of the KOS engine classification,so as to provide the new thought for automatic classification research. |
| |
| Keywords: | automatic classification knowledge organization system machine learning BP neural network |
|
| 点击此处可从《图书情报工作》浏览原始摘要信息 |
| 点击此处可从《图书情报工作》下载免费的PDF全文 |
|
