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   

Examining the Library as a Site for Intervention: A Mixed-Methods Case Study Evaluation of the “Innovative Solutions to Homelessness” Project     

Teresa Hill  Katherine A. Tamminen 《图书馆管理杂志》2020,60(5):470-492

Abstract

This study examined a project that delivered social work services to homeless individuals. A mixed-methods case study was conducted using quantitative and qualitative data from 93 library employees and the project’s Homelessness Prevention Outreach Worker (HPOW). There was an increase in the number of clients accessing community supports during the project, and the HPOW was integral to the provision of support and resources to homeless individuals. Staff training was associated with significantly greater knowledge, comfort, and skills in working with homeless individuals. These findings can inform the delivery and implementation of similar programs for homeless individuals.  相似文献   

基于知识元的学术论文内容创新性智能化评价研究   总被引：1，自引：0，他引：1  

李贺  杜杏叶 《图书情报工作》2020,64(1):93-104

[目的/意义] 创新性是对学术论文质量最基本的要求，是学术论文的灵魂，是学术论文评价的核心。知识元是学术论文基本组成单元。基于知识元理论和机器学习相关理论与算法，从学术论文内容层面研究计算机如何智能化地进行创新性评价及其实现过程与方法。[方法/过程] 首先，构建学术论文的研究问题、理论、方法、结论4个知识元本体，接着提出基于知识元的学术论文创新性判断模型。其次，根据学术论文研究特点，构建理论与方法机器分类模型及知识元的抽取规则与抽取方法，建立规则库和知识语料库。最后，基于语义相似度计算方法，根据判断规则和相关权重对学术论文4个维度的创新性进行评分。[结果/结论] 基于知识元抽取的学术论文创新性评分系统的实证结果表明，该智能化评价方法具有一定的可行性，可为学术论文内容创新性智能化评价系统的最终实现提供方法借鉴。  相似文献   

美国《图书馆杂志》“年度图书馆”奖获得者服务特色分析     

谈大军  王梦迪 《图书情报工作》2020,64(7):145-152

[目的/意义] 对美国《图书馆杂志》从1992年开始设立的"年度图书馆"奖的评选标准以及获奖图书馆的特色服务进行研究，旨在为我国图书馆开展特色化服务提供借鉴。[方法/过程] 通过网络调查法和案例分析法，对2000-2018年获得"年度图书馆"奖的19所图书馆开展的特色服务进行比较分析。[结果/结论] 获奖图书馆的服务特色：重视公民教育，强化教育职能；强调均等服务理念，体现人文关怀；提供多元社区信息服务，参与社区建设；树立品牌意识，打造品牌项目。对我国图书馆界的启示：科学合理地进行角色定位；积极参与社区贫困计划；强化特色服务品牌意识；拓宽合作领域。  相似文献   

一种基于图卷积自编码模型的多维度学科知识网络融合方法     

李慧  胡吉霞 《图书情报工作》2020,64(18):114-125

[目的/意义] 针对包含单一类型知识单元的知识网络难以全面反映学科知识结构的问题，提出一种从多维度进行知识网络结构融合的方法，为学科领域知识结构挖掘提供借鉴。[方法/过程] 利用LDA及TF-IDF方法抽取学科知识单元，然后运用语义相似度和关键词共现分析方法构建3个学科知识子网络：主题网络、关键词网络和实体网络，并采用空间节点传递对齐方法对齐子网络节点，接着设计基于图卷积操作的自编码模型对知识节点进行表示，最后通过计算余弦相似度重构学科知识网络。[结果/结论] 实验部分以人工智能领域为例，构建融合主题、关键词和实体的学科知识网络并展开分析，实验结果表明，本文所提方法能有效地揭示学科领域研究内容和知识结构，为学科知识发现与组织研究提供有益参考。  相似文献   

学术乃天下之公器——哈佛燕京图书馆馆长郑炯文访谈     

谢欢 《中国图书馆学报》2020,46(4):126-131

2019年7月22日,南京大学谢欢博士对哈佛燕京图书馆馆长郑炯文先生就北美东亚图书馆发展相关问题进行访谈。东亚图书馆肇始于欧洲,起源于传教士对文史哲印刷文献的专题收集,与汉学发展紧密相关；美国东亚图书馆在第二次世界大战后取得了快速的发展,如今美国已成为西方世界东亚研究的中心。华人图书馆员是北美东亚图书馆从业人员中非常重要的群体,三代华人图书馆员各具专长,为北美东亚图书馆发展做出了贡献。郑炯文先生自担任哈佛燕京图书馆馆长以来,主要致力于以下三方面工作:①整理裘开明、吴文津担任馆长期间收集的文献；②开放馆藏,将哈佛燕京图书馆的资源面向全世界学者开放；③推动中美图书馆员交流合作项目。  相似文献   

《左传》的文本之争与文本流变     

郭彩萍  李金荣 《图书馆论坛》2020,(6):128-135

《左传》是我国首部以编年为次序、以鲁国十二公为传主,系统记述春秋战国时期历史,对中国文化产生了巨大影响的文史作品。文章在概述《左传》文化价值的基础上,梳理了两千多年来关于《左传》文本与作者的主要学术争论,甄别《左传》流变过程中的22个关键文本。  相似文献   

体育与健康的研究综述     

张朝翔 《当代体育科技》2020,(11):10-11

全民都获取全面的健康是能否成为强国的重要标准之一,是"以人为本"的基本体现。在健康中国行动的背景下,国家越来越重视以体育健身来促进人民的健康发展,也相继出台了一系列关于全民健康相关的文件和纲要。本文通过对国内国外研究现状进行了分析,通过对体育健康的梳理,了解体育健康目前发展现状,分析不足之处,为体育健康在以后的界定打下基础。  相似文献