一种新颖的基于量化概念格的属性归纳算法

王德兴; 胡学钢; 刘晓平

您当前的位置：

首页 >

文章列表页 >

一种新颖的基于量化概念格的属性归纳算法

更新时间：2025-12-08

- 一种新颖的基于量化概念格的属性归纳算法
- Issue 2, Pages: 176-179(2007)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP182
- Online First：10 February 2007，
  
  Published：2007
- 稿件说明：
移动端阅览
王德兴, 胡学钢, 刘晓平. 一种新颖的基于量化概念格的属性归纳算法[J]. 2007, (2): 176-179.
DOI：

王德兴, 胡学钢, 刘晓平. 一种新颖的基于量化概念格的属性归纳算法[J]. 2007, (2): 176-179. DOI：

摘要

为了解决数据挖掘过程中挖掘的知识粒度过粗或过细问题

并利用概念格的偏序特性

提出了一种基于量化概念格的属性归纳算法.首先对概念格的外延进行量化

得到量化概念格

再根据概念格的哈斯图

采用概念的爬升进行相应的泛化

从而获得基于量化概念格的多层、多属性归纳.与面向属性归纳(AOI)算法相比较

结果表明所提算法不仅能实现AOI的单一属性归纳

还能进行多层、多属性的归纳

其属性泛化的路径不是惟一的

并且很容易在量化概念格的哈斯图中寻找合适的泛化路径和阈值

以此得到用户要求的、合理的属性归纳结果.

Abstract

In order to deal with the problem of over-coarse or over-fine knowledge granularity in data mining

an attribute induction algorithm based on quantized concept lattice is proposed by using the partial property of the concept lattice. Firstly

the quantized concept lattice is defined by quantifying concept extension of the concept lattice

and then it is generalized using concept ascension according to the Hasse diagram of the concept lattice so as to get the induction with multi-level and multi-attribute based on the quantized concept lattice. Compared with the attribute-oriented induction(AOI)algorithm

the proposed algorithm can not only perform the unitary induction of AOI

but also carry out the induction with multi-level and multi-attribute

and the path of attribute generalization is not unique. Moreover

it is easy to find proper generalized paths and thresholds in Hasse diagram of quantized concept lattice to obtain the reasonable results required by users.

关键词

Keywords

references

{"db_type":"CJFDREF","db_name":"期刊","reference_articles":[{"unit":"电子学报","flag":"[J]","issue":"02","year":2005,"author":"强宇,刘宗田,林炜,时百胜,李云","index":1,"title":"模糊概念格在知识发现的应用及一种构造算法"},{"unit":"计算机科学","flag":"[J]","issue":"03","year":2001,"author":"刘明吉;王秀峰;李宝林","index":2,"title":"基于多层次概念提升的知识发现方法"},{"unit":"计算机研究与发展","flag":"[J]","issue":"02","year":2001,"author":"陈红梅,王丽珍","index":3,"title":"面向属性的量化归纳"},{"unit":"软件学报","flag":"[J]","issue":"07","year":1999,"author":"周生炳,张钹,成栋","index":4,"title":"基于规则面向属性的数据库归纳的无回溯算法"}],"articles_count":4}

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

两阶段密度意识子空间聚类模型

海量信息异常检测问题的异常概率排序算法

Influence of Structural Parameters on the Summer Operational Characteristics of a Three-Tower-in-One Indirect Air-Cooling System

Numerical Simulation of Heat-Moisture Barrier Performance of a Horizontal Air Curtain in Cold Storage

Knowledge Graph Representation Learning Driven by Semantic Discrimination and Subgraph Integration

Related Author

李长路

王劲林

郭志川

潘梁

陈刚

蔡远利

穆静

杨卫丽

Related Institution

中国科学院声学研究所国家网络新媒体工程技术研究中心

中国科学院大学

西安交通大学电子与信息工程学院

中国国防科技信息中心

⁰