Use of generalized one-sided FCA approach for joining of simple object-attribute models

P. Butka, J. Pócsová, J. Pócs
{"title":"Use of generalized one-sided FCA approach for joining of simple object-attribute models","authors":"P. Butka, J. Pócsová, J. Pócs","doi":"10.1109/SACI.2013.6608992","DOIUrl":null,"url":null,"abstract":"In this paper we describe the possibility for usage of generalized version of one-sided (fuzzy) concept lattices, which represents analytical method from the area of Formal Concept Analysis (FCA), for joining of several simple object-attribute models. The main advantage of the algorithm for (so-called) Generalized One-sided Concept Lattices (GOSCL) is its possibility or ability to work with various attributes types. Sometimes, the analyst needs to join some object-attribute models into one comprehensive structure, he/she is able to do it using generalized FCA approach in two basic ways, which are described within the paper. Both approaches provides isomorphic outputs, but provision of information can be different due to usage of generalized attributes, what leads to benefits like better interpretation and understanding of output models and data.","PeriodicalId":304729,"journal":{"name":"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 8th International Symposium on Applied Computational Intelligence and Informatics (SACI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SACI.2013.6608992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In this paper we describe the possibility for usage of generalized version of one-sided (fuzzy) concept lattices, which represents analytical method from the area of Formal Concept Analysis (FCA), for joining of several simple object-attribute models. The main advantage of the algorithm for (so-called) Generalized One-sided Concept Lattices (GOSCL) is its possibility or ability to work with various attributes types. Sometimes, the analyst needs to join some object-attribute models into one comprehensive structure, he/she is able to do it using generalized FCA approach in two basic ways, which are described within the paper. Both approaches provides isomorphic outputs, but provision of information can be different due to usage of generalized attributes, what leads to benefits like better interpretation and understanding of output models and data.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用广义单侧FCA方法连接简单对象-属性模型
本文描述了用广义的单侧(模糊)概念格的可能性,它代表了形式概念分析(FCA)领域的分析方法,用于连接几个简单的对象-属性模型。对于(所谓的)广义单侧概念格(GOSCL)的算法的主要优点是它可以或能够处理各种属性类型。有时,分析人员需要将一些对象-属性模型连接到一个综合结构中,他/她可以使用广义FCA方法在两种基本方法中做到这一点,这在本文中进行了描述。这两种方法都提供同构输出,但是由于使用了一般化属性,提供的信息可能会有所不同,这可以带来更好地解释和理解输出模型和数据等好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
V/f control strategy with constant power factor for SPMSM drives, with experiments Spline filtering in accordance to ISO/TS 16610: ANSI C-code for engineers HITS based network algorithm for evaluating the professional skills of wine tasters Performance evaluation of a face detection algorithm running on general purpose operating systems Tumor growth model identification and analysis in case of C38 colon adenocarcinoma and B16 melanoma
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1