Debiaser for Multiple Variables to enhance fairness in classification tasks     

《Information processing & management》2023,60(2):103226

Nowadays assuring that search and recommendation systems are fair and do not apply discrimination among any kind of population has become of paramount importance. This is also highlighted by some of the sustainable development goals proposed by the United Nations. Those systems typically rely on machine learning algorithms that solve the classification task. Although the problem of fairness has been widely addressed in binary classification, unfortunately, the fairness of multi-class classification problem needs to be further investigated lacking well-established solutions. For the aforementioned reasons, in this paper, we present the Debiaser for Multiple Variables (DEMV), an approach able to mitigate unbalanced groups bias (i.e., bias caused by an unequal distribution of instances in the population) in both binary and multi-class classification problems with multiple sensitive variables. The proposed method is compared, under several conditions, with a set of well-established baselines using different categories of classifiers. At first we conduct a specific study to understand which is the best generation strategies and their impact on DEMV’s ability to improve fairness. Then, we evaluate our method on a heterogeneous set of datasets and we show how it overcomes the established algorithms of the literature in the multi-class classification setting and in the binary classification setting when more than two sensitive variables are involved. Finally, based on the conducted experiments, we discuss strengths and weaknesses of our method and of the other baselines.  相似文献   

Artificial intelligence implication on energy sustainability in Internet of Things: A survey     

《Information processing & management》2023,60(2):103212

The massive number of Internet of Things (IoT) devices connected to the Internet is continuously increasing. The operations of these devices rely on consuming huge amounts of energy. Power limitation is a major issue hindering the operation of IoT applications and services. To improve operational visibility, Low-power devices which constitute IoT networks, drive the need for sustainable sources of energy to carry out their tasks for a prolonged period of time. Moreover, the means to ensure energy sustainability and QoS must consider the stochastic nature of the energy supplies and dynamic IoT environments. Artificial Intelligence (AI) enhanced protocols and algorithms are capable of predicting and forecasting demand as well as providing leverage at different stages of energy use to supply. AI will improve the efficiency of energy infrastructure and decrease waste in distributed energy systems, ensuring their long-term viability. In this paper, we conduct a survey to explore enhanced AI-based solutions to achieve energy sustainability in IoT applications. AI is relevant through the integration of various Machine Learning (ML) and Swarm Intelligence (SI) techniques in the design of existing protocols. ML mechanisms used in the literature include variously supervised and unsupervised learning methods as well as reinforcement learning (RL) solutions. The survey constitutes a complete guideline for readers who wish to get acquainted with recent development and research advances in AI-based energy sustainability in IoT Networks. The survey also explores the different open issues and challenges.  相似文献   

共享经济可持续性评价：社会感知与客观绩效     

董晓松  霍依凡  赵星 《科研管理》2023,44(1):79-88

共享经济行业可持续性评价的社会感知和客观绩效不一致将造成认知错位、投资误判和政策失效等结果。本文在线挖掘2017—2019年我国主要社交媒体上29 771条文本信息，并收集行业统计数据，综合测度共享经济行业的可持续性并比较其差异。研究发现：社会公众并不认为共享经济行业具有显著的总体可持续性，而且行业实际绩效展现的可持续性与社会大众认知截然不同。进一步发现：受限于主观认知能力，社会公众认为共享经济可持续性主要来自可观察到的行业外部经济和外部生态等维度，但客观绩效表明共享经济行业内部的经济和外部的技术优势才是其可持续性的重要支撑。此外，二者评价的差异在住宿与医疗等产能共享内部过程不易被大众观察的行业中最为突出。  相似文献   

Exploring an intervention’s impact on everyday school activities     

Marianne Björn  Idor Svensson 《Support for Learning》2021,36(1):5-19

The focus of this paper is on a group of pupils with reading and writing difficulties who have been participating in an intervention study using assistive technology. That intervention study contained supervised training sessions with reading and writing tasks using an iPad with special supportive applications. The current study is a qualitative investigation of whether there has been any transfer from the intervention, to the pupils’ everyday school activities. Interviews with pupils and their teachers and observations during classroom lectures have been used to collect data. The results show that the pupils were positive to the assistive technology (the applications on the iPads), they found the apps easy to learn how to use and they appreciated the benefits they could give. Even so, only a few of the pupils had found use for and continued to use the tools after the intervention period finished. Possible reasons are that when the novelty wore off, students reverted to their usual study habits and that older students with many teachers and different classrooms were less able to adapt to using the apps. To improve transfer, it is suggested to introduce assistive technology earlier to students, in the younger grades, before study habits have been formed and to inform teachers about the use of AT in the classroom, including what is available and how it can benefit students.  相似文献   

Analyzing Food Science Research for Publishing Characteristics as a Model for Understanding the Needs of Researchers     

Lutishoor Salisbury  Jeremy J. Smith  Abayomi Omotola Omolewu 《资料收集管理》2020,45(4):335-353

Abstract

This paper provides a methodology to study the characteristics of the research output from a university department. The faculty publications and their cited references over a 10-year period were used as the basis for this study to identify their publishing patterns and the types of material they are publishing; a core set of journals and other resources they are publishing in and citing over this period; the characteristics of the journals in which they publish and cite; the degree of openness of their publications and their citation advantage; and the age of resources that are referenced.  相似文献   

The Impact of More,Better, Faster,Cheaper: How the PCC Influenced Everything That Followed     

Carol G. Hixson 《Cataloging & classification quarterly》2020,58(3-4):294-302

Abstract

The beginnings and the early years of the Program for Cooperative Cataloging (PCC) had a profound impact on the approach taken to cataloging in North America and around the world. The commitment to standards, cooperation, and expanded access also had an impact that went far beyond cataloging operations. One library dean traces the evolution of her vision and contemplates how the PCC’s principles have shaped her entire career and have affected the libraries in which she has worked.  相似文献   

公共文化服务大数据集成架构设计研究   总被引：1，自引：0，他引：1  

化柏林  赵东在  申泳国 《图书情报工作》2020,64(10):3-11

[目的/意义] 针对当前各图书馆、文化馆等公共文化服务机构的多源异构数据，设计出一套行之有效的集成架构。[方法/过程] 在充分分析公共文化大数据资源的基础上，对公共文化服务大数据的类型与分布进行分析，结合公共文化服务大数据的应用场景，设计公共文化大数据集成的架构。[结果/结论] 提出一个由数据来源层、系统集成层、数据融合层、存储层、应用层五个层次构成的公共文化服务大数据集成架构，并对其中的采集、存储等关键技术进行研究。  相似文献   

我国政府大数据政策价值取向的分析研究     

陈慧  王晓晓  段尧清 《图书情报工作》2020,64(11):19-27

[目的/意义] 大数据政策是大数据应用和发展的推动力量，其价值取向分析可以为我国政府大数据政策的制定、执行和评估提供借鉴，为大数据政策未来的发展方向提供依据。[方法/过程] 收集国务院及其各部门门户网站发布的政务大数据政策文本共计58份，运用主题分析方法对政策文本中表达政务大数据价值取向的主题进行编码分析，编码过程以NVivo12软件为辅助工具。[结果/结论] 通过主题分析，构建大数据政策价值取向总体框架，框架总结政治、经济、社会、生态与科技5个维度的价值取向，并探讨各维度及其具体价值取向间的交互关系。  相似文献   

数据管理与数据治理的比较分析及其对制定科学数据开放共享政策的启示     

盛小平  宋大成 《图书情报工作》2020,64(22):4-10

[目的/意义] 比较分析数据管理与数据治理差异与联系，为制定科学数据开放共享政策提供参考。[方法/过程] 运用比较分析法，解析数据管理与数据治理在定义与内涵、功能、目标、原则、焦点领域5个方面的异同，由此解析其对制定我国科学数据开放共享政策的启示。[结果/结论] 数据管理与数据治理在定义与内涵、功能、目标、原则、焦点领域上都有显著差异，但两者也有内在联系。数据治理是成功实施数据管理的关键。认清两者的关系有助于明晰目前我国科学数据管理政策的不足之处，为今后完善科学数据管理办法提供参考，从而规划与制定实用的科学数据开放共享细则。  相似文献   

武汉大学面向本科生的数据素养通识课程的建设与思考     

刘霞  方小利  郑怡萍 《图书情报工作》2020,64(22):69-76

[目的/意义] 旨在通过分享武汉大学数据素养通识课程的建设过程，为同行开展相关工作提供参考。[方法/过程] 通过案例分析、数据统计和数据挖掘可视化方法对"武大通识3.0"背景下的《数据素养与数据利用》课程的教学目标、教学内容、教学特色以及教学效果进行分析，探索课程体系的合理性。[结果/结论] 授课方式和课内外实践内容的设置能够很好地调动学生学习的积极性，提高学习效果；课程考核结果、学生学习前后的问卷调查及课后反馈表明，课程学习明显提升了学生的数据素养。  相似文献