通过应用机器学习来检测和减少数据浪费,提高信息系统的可持续性

IF 1.7 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Bastin Tony Roy Savarimuthu, Jacqueline Corbett, Muhammad Yasir, Vijaya Lakshmi
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引用次数: 0

摘要

大数据是创造信息价值的重要基石。然而,信息系统日益受到无用和浪费数据的困扰,这些数据可能妨碍信息系统的有效利用并威胁到可持续性目标。使用建设性的设计科学方法,这项工作首先定义了数字数据浪费。然后,开发一个包含两个组件的集成工件。第一个组件包括13个用于检测数据浪费的机器学习模型。将这些数据应用到两个领域的35576条在线评论中,我们发现餐馆评论的数据浪费率为1.9%,而应用评论的数据浪费率为35.8%。机器学习可以准确识别83% ~ 99.8%的数据浪费;深度学习模型尤其有前景,准确率在96.4%到99.8%之间。第二个组成部分包括可持续性成本计算器,用于量化减少数据浪费的社会、经济和环境效益。消除样本中5948个无用的审查将节省6.9个工时,服务器、中间件和客户机成本2.93美元,以及9.52千克的碳排放。将这些结果外推到互联网上的评论,可以显示出更大的节省。这项工作通过强调数据浪费问题的新类别和设计解决这一问题的方法,有助于与可持续信息系统相关的设计知识。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Information Systems Sustainability by Applying Machine Learning to Detect and Reduce Data Waste
Big data are key building blocks for creating information value. However, information systems are increasingly plagued with useless, waste data that can impede their effective use and threaten sustainability objectives. Using a constructive design science approach, this work first, defines digital data waste. Then, it develops an ensemble artifact comprising two components. The first component comprises 13 machine learning models for detecting data waste. Applying these to 35,576 online reviews in two domains reveals data waste of 1.9% for restaurant reviews compared to 35.8% for app reviews. Machine learning can accurately identify 83% to 99.8% of data waste; deep learning models are particularly promising, with accuracy ranging from 96.4% to 99.8%. The second component comprises a sustainability cost calculator to quantify the social, economic, and environmental benefits of reducing data waste. Eliminating 5948 useless reviews in the sample would result in saving 6.9 person hours, $2.93 in server, middleware and client costs, and 9.52 kg of carbon emissions. Extrapolating these results to reviews on the internet shows substantially greater savings. This work contributes to design knowledge relating to sustainable information systems by highlighting the new class of problem of data waste and by designing approaches for addressing this problem.
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来源期刊
Communications of the Association for Information Systems
Communications of the Association for Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
3.90
自引率
20.00%
发文量
35
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