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   

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   

Ghost writer in the machine: the politics of determining the machinic/expressive functions of software     

Daniel M. Sutko 《传播与批判/文化研究》2018,15(1):18-34

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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 Program for Cooperative Cataloging’s Transformative Role as a Leader of Change     

Philip E. Schreur 《Cataloging & classification quarterly》2020,58(3-4):397-402

Abstract

The transformation of library metadata encoded in MARC to linked data will enable libraries to participate in the Semantic Web. This transformation, however, will be an iterative development dependent upon community-based decisions. The PCC, as a community-based organization, is ideally positioned to lead this transformation. As PCC guides this transition, three broad areas must be resolved: the conversion of legacy data to linked data, the use of identifiers to support controlled headings, and the transformation of current workflows to linked-data counterparts. By embracing the Web as a community, PCC can confirm its relevance in a complex web of global data.  相似文献   

高校图书馆中华传统文化立体阅读推广探究——以北京师范大学图书馆“二十四节气”阅读推广为例     

孙媛媛  张玲  于静  张珅 《图书情报工作》2020,64(9):57-64

[目的/意义] 以北京师范大学图书馆"二十四节气"传统文化立体阅读推广为例，探讨基于中华传统文化的高校图书馆立体阅读推广模式。[方法/过程] 论述高校图书馆开展中华传统文化阅读推广的意义及采用立体阅读模式的必要性，从活动准备、活动内容和特点、活动效果评价三方面阐述北京师范大学图书馆"二十四节气"传统文化阅读推广工作。[结果/结论] 提出高校图书馆以立体阅读模式开展中华传统文化阅读推广的策略。  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   

澳大利亚数字人文项目透视——兼论对我国数字人文项目的启示     

徐彤阳  杨明睿 《图书情报工作》2020,64(22):145-152

[目的/意义] 分析澳大利亚数字人文项目特征，总结澳大利亚数字人文项目概况，获取对我国数字人文的建设性意见。[方法/过程] 运用网络调查法和访谈法对澳大利亚数字人文项目开展情况进行分析，总结项目概况并梳理其发展阶段和各阶段代表性项目，按照研究方法和方向的不同进行分类，同时根据项目成果和影响力建立分析评价体系来获取有价值的特征，并据此讨论为丰富我国数字人文建设的理论和实践提供借鉴的诸多意见。[结果/结论] 澳大利亚数字人文项目整体阶段特征明显、意义显著，本文总结出其项目的社会服务、图书馆深度参与、创新合作共享等特征，针对我国数字人文提出加大投入、释放图书馆潜力和形成特色的主要意见。  相似文献   

专题情报数据管理与智能分析平台的构建     

于倩倩  钱力  程冰  常志军  王慧丽  靳茜 《图书情报工作》2020,64(24):92-105

[目的/意义] 面对多学科领域、多类型用户的专题情报服务需求，建立专题情报数据管理与智能分析平台。实现专题情报分析的流程化和智能化，同时对融入专家智慧的专题情报分析过程数据进行管理，丰富服务模式，提升服务需求响应速度。[方法/过程] 在调研已有相关研究与实践分析基础上，提出平台设计思路、建设框架，对平台主要功能和关键技术进行剖析。[结果/结论] 专题情报数据管理与智能分析平台已建设完成。平台集成了多来源多类型数据，打通了从数据到分析的服务链条。嵌入了多种情报分析方法和深度学习算法，实现了多维多层次分析服务。能够对分析过程和情报分析人员历史积累数据进行管理，实现数据共享和重复利用。  相似文献