基于特征工程的数据仓库研究综述

Lipsa Das, Laxmi Ahuja, V. Chauhan, Akanksha Singh
{"title":"基于特征工程的数据仓库研究综述","authors":"Lipsa Das, Laxmi Ahuja, V. Chauhan, Akanksha Singh","doi":"10.1109/iciptm54933.2022.9754137","DOIUrl":null,"url":null,"abstract":"Today is an era of online shopping and most of the persons are willing to buy things via internet. The reason behind this they can get lots of options in a single click, there is no need to waste time to waiting up in the queue as well. It is becoming more common in our daily lives. There are lots of algorithms which understand the user's interests and behavior regarding this. In this paper we are presenting feature engineering concept to predict the behavior of customer. Feature engineering allows us to create feature by our self which can be applied on any area. It includes the different stage of process to create feature and after creating the feature in any domain machine learning algorithm can be applied. Data warehousing is also essential to predict any behavior on event and by selecting any event it is easy to take the decision on any event and these predictions can be based on any day or week or months which are also very helpful from industry point of view.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"7 1","pages":"690-696"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Review of Data Warehousing Using Feature Engineering\",\"authors\":\"Lipsa Das, Laxmi Ahuja, V. Chauhan, Akanksha Singh\",\"doi\":\"10.1109/iciptm54933.2022.9754137\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Today is an era of online shopping and most of the persons are willing to buy things via internet. The reason behind this they can get lots of options in a single click, there is no need to waste time to waiting up in the queue as well. It is becoming more common in our daily lives. There are lots of algorithms which understand the user's interests and behavior regarding this. In this paper we are presenting feature engineering concept to predict the behavior of customer. Feature engineering allows us to create feature by our self which can be applied on any area. It includes the different stage of process to create feature and after creating the feature in any domain machine learning algorithm can be applied. Data warehousing is also essential to predict any behavior on event and by selecting any event it is easy to take the decision on any event and these predictions can be based on any day or week or months which are also very helpful from industry point of view.\",\"PeriodicalId\":6810,\"journal\":{\"name\":\"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)\",\"volume\":\"7 1\",\"pages\":\"690-696\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iciptm54933.2022.9754137\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iciptm54933.2022.9754137","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

今天是一个网上购物的时代,大多数人都愿意通过互联网买东西。这背后的原因是,他们可以在一次点击中获得很多选项,也不需要浪费时间排队等待。它在我们的日常生活中变得越来越普遍。有很多算法可以理解用户的兴趣和行为。本文提出了特征工程的概念来预测顾客的行为。特征工程允许我们自己创建可以应用于任何领域的特征。它包括创建特征过程的不同阶段,在任何领域创建特征后都可以应用机器学习算法。数据仓库对于预测事件上的任何行为也是必不可少的,通过选择任何事件,就可以很容易地对任何事件做出决定,这些预测可以基于任何一天、任何一周或任何一个月,从行业的角度来看,这也非常有帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Review of Data Warehousing Using Feature Engineering
Today is an era of online shopping and most of the persons are willing to buy things via internet. The reason behind this they can get lots of options in a single click, there is no need to waste time to waiting up in the queue as well. It is becoming more common in our daily lives. There are lots of algorithms which understand the user's interests and behavior regarding this. In this paper we are presenting feature engineering concept to predict the behavior of customer. Feature engineering allows us to create feature by our self which can be applied on any area. It includes the different stage of process to create feature and after creating the feature in any domain machine learning algorithm can be applied. Data warehousing is also essential to predict any behavior on event and by selecting any event it is easy to take the decision on any event and these predictions can be based on any day or week or months which are also very helpful from industry point of view.
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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信