利用扩展关联规则网络探索数据

2018 7th Brazilian Conference on Intelligent Systems (BRACIS) Pub Date : 2018-10-01 DOI:10.1109/bracis.2018.00064

Renan de Padua, Dario Brito Calçada, Verônica Oliveira de Carvalho, Solange Oliveira Rezende

{"title":"利用扩展关联规则网络探索数据","authors":"Renan de Padua, Dario Brito Calçada, Verônica Oliveira de Carvalho, Solange Oliveira Rezende","doi":"10.1109/bracis.2018.00064","DOIUrl":null,"url":null,"abstract":"In this paper, we presented the Extended Association Rule Network (ExARN) to structure, prune and analyze a set of association rules, aiming to build hypothesis candidates. The ExARN extends the ARN, proposed by [2], allowing a more complete exploration. We validate the ExARN using two databases: contact lenses and hayes-roth, both available online for download. The results were validated by comparing the ExARN to the conventional ARN and also by comparing the results with a decision tree algorithms. The approach presented promising results, showing its capability to explain a set of objective items, aiding the user on the hypothesis building.","PeriodicalId":405190,"journal":{"name":"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)","volume":"34 7","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Exploring the Data Using Extended Association Rule Network\",\"authors\":\"Renan de Padua, Dario Brito Calçada, Verônica Oliveira de Carvalho, Solange Oliveira Rezende\",\"doi\":\"10.1109/bracis.2018.00064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we presented the Extended Association Rule Network (ExARN) to structure, prune and analyze a set of association rules, aiming to build hypothesis candidates. The ExARN extends the ARN, proposed by [2], allowing a more complete exploration. We validate the ExARN using two databases: contact lenses and hayes-roth, both available online for download. The results were validated by comparing the ExARN to the conventional ARN and also by comparing the results with a decision tree algorithms. The approach presented promising results, showing its capability to explain a set of objective items, aiding the user on the hypothesis building.\",\"PeriodicalId\":405190,\"journal\":{\"name\":\"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)\",\"volume\":\"34 7\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/bracis.2018.00064\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 7th Brazilian Conference on Intelligent Systems (BRACIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/bracis.2018.00064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 3

摘要

在本文中，我们提出了扩展关联规则网络(ExARN)来构建、修剪和分析一组关联规则，旨在建立假设候选。ExARN扩展了[2]提出的ARN，允许更完整的探索。我们使用两个数据库来验证ExARN:隐形眼镜数据库和hayes-roth数据库，这两个数据库都可以在线下载。通过将ExARN与传统的ARN进行比较，并将结果与决策树算法进行比较，验证了结果。该方法呈现出令人鼓舞的结果，显示出其解释一组客观项目的能力，帮助用户建立假设。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Exploring the Data Using Extended Association Rule Network

In this paper, we presented the Extended Association Rule Network (ExARN) to structure, prune and analyze a set of association rules, aiming to build hypothesis candidates. The ExARN extends the ARN, proposed by [2], allowing a more complete exploration. We validate the ExARN using two databases: contact lenses and hayes-roth, both available online for download. The results were validated by comparing the ExARN to the conventional ARN and also by comparing the results with a decision tree algorithms. The approach presented promising results, showing its capability to explain a set of objective items, aiding the user on the hypothesis building.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2018 7th Brazilian Conference on Intelligent Systems (BRACIS)

自引率

0.00%

发文量