WORKSHOP: Doctoral Consortium at the 2016 ACM User Modeling, Adaptation and Personalization Conference (UMAP 2016)

研讨会:2016 年 ACM 用户建模、适应和个性化会议上的博士联盟 (UMAP 2016)

基本信息

  • 批准号:
    1642486
  • 负责人:
  • 金额:
    $ 1.44万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-07-01 至 2017-06-30
  • 项目状态:
    已结题

项目摘要

This is funding to support travel for up to 12 students enrolled in PhD programs in U.S. institutions, to present their accepted papers and posters and/or to attend the Doctoral Consortium associated with the 24th International Conference on User Modeling, Adaptation and Personalization (UMAP 2016), to be held at Dalhousie University in Halifax, Nova Scotia (Canada) on July 13-17, and which is sponsored by ACM SIGCHI and SIGWEB. User interfaces that adapt themselves to available user information (such as special needs or individual preferences) are becoming increasingly important, so much so that adaptability has become a selling point for software products. A system with the ability to construct and consult a user model (an explicit representation of properties of a particular user or group of users) can adapt diverse aspects of its performance and enhance its effectiveness, usability and/or acceptance in a variety of situations (e.g., to reduce information overload, to improve the quality of information retrieval, filtering and annotation, and to generate useful information visualizations). Applications for user modeling range from electronic commerce and intelligent learning environments to health care and assistive technologies. Relevant platforms for user modeling include mobile and wearable systems and smart environments, as well as individual desktop systems, groupware, adaptive hypermedia, and other web-based systems. The annual UMAP conference is the premier forum at which academic and industrial researchers from all these fields gather to present their latest research and to exchange their complementary insights on user modeling issues. More information about the conference is available online at http://www.um.org/umap2016/. Attending and presenting their work at UMAP will have a significant impact on the careers of the future generation of user modeling, adaptation, and personalization researchers. First, they will have the opportunity to present their work to a knowledgeable audience and through lively discussions get useful comments at an early stage of their research when it will be most useful. Just as importantly, they will have a chance to meet established researchers and other graduate students doing similar work, to exchange ideas and to make contacts that will be invaluable to them as they progress in their scientific careers. Interacting with young researchers is also beneficial to experienced investigators, by providing fresh ideas and new perspectives. Thus, the Doctoral Consortium is a great confidence builder for the students involved, and highly stimulating to the senior researchers as well. Many past participants in the UMAP Doctoral Consortium have gone on to become well-regarded researchers and practitioners in the field. Students whose work has been selected for presentation at the Doctoral Consortium will benefit from that experience in a number of additional ways. They will be invited to write a paper that will be published in the UMAP 2016 conference proceedings, which will be included in the ACM Digital Library. They will have 15 minutes to present their work (which may include a short demonstration if appropriate), to be followed by an additional 15 minutes for questions and discussion. During the question/discussion period and in subsequent informal interactions, organizing committee members and other participants will provide constructive comments on each student's work and attempt to address aspects on which the student has requested advice. The organizers have reaffirmed the long-standing and demonstrated UMAP commitment to diversity; to this end, they will make special efforts to recruit women and members of under-represented groups when selecting the candidates to receive financial support.
这笔资金用于支持最多12名在美国院校注册博士项目的学生的旅费,展示他们被接受的论文和海报,和/或参加与第24届用户建模、适应和个性化国际会议(UMAP 2016)相关的博士联盟,该会议将于7月13-17日在加拿大新斯科舍省哈利法克斯的Dalhousie大学举行,由ACM SIGCHI和SIGWEB赞助。适应可用的用户信息(如特殊需求或个人偏好)的用户界面正变得越来越重要,以至于适应性已成为软件产品的一个卖点。具有构建和咨询用户模型(特定用户或用户组的属性的显式表示)的能力的系统可以适应其性能的不同方面,并在各种情况下增强其有效性、可用性和/或接受性(例如,以减少信息过载、提高信息检索、过滤和注释的质量,以及生成有用的信息可视化)。用户建模的应用范围从电子商务和智能学习环境到医疗保健和辅助技术。用户建模的相关平台包括移动和可穿戴系统和智能环境,以及个人桌面系统、群件、自适应超媒体和其他基于Web的系统。一年一度的UMAP会议是来自所有这些领域的学术和行业研究人员聚集在一起展示他们的最新研究成果并就用户建模问题交换互补见解的主要论坛。欲了解更多有关这次会议的信息,请访问http://www.um.org/umap2016/.。参加并在UMAP上展示他们的工作将对下一代用户建模、适应和个性化研究人员的职业生涯产生重大影响。首先,他们将有机会向知识渊博的观众介绍他们的工作,并通过积极的讨论在他们的研究的早期阶段获得有用的评论,当它将是最有用的。同样重要的是,他们将有机会与从事类似工作的知名研究人员和其他研究生见面,交流思想,建立联系,这些对他们在科学事业中的进步将是无价的。通过提供新的想法和新的视角,与年轻的研究人员互动也对经验丰富的研究人员有利。因此,博士团对参与其中的学生来说是一个很好的信心建立者,对高级研究人员也是非常有刺激性的。UMAP博士联盟的许多过去的参与者后来成为该领域备受尊敬的研究人员和实践者。被选中在博士生联合会上发表作品的学生将在许多其他方面从这一经历中受益。他们将被邀请撰写一篇论文,发表在UMAP 2016年会议论文集上,该论文集将被纳入ACM数字图书馆。他们将有15分钟的时间介绍他们的工作(如果合适的话,可能包括一个简短的演示),然后再有15分钟的时间进行提问和讨论。在提问/讨论期间和随后的非正式互动中,组委会成员和其他参与者将对每个学生的工作提出建设性的意见,并试图解决学生要求提供建议的方面。组织者重申了UMAP长期以来对多样性的承诺;为此,他们将在挑选候选人接受财政支助时特别努力招募妇女和代表性不足群体的成员。

项目成果

期刊论文数量(0)
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会议论文数量(0)
专利数量(0)

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Sidney D'Mello其他文献

Sidney D'Mello的其他文献

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{{ truncateString('Sidney D'Mello', 18)}}的其他基金

Collaborative Research [FW-HTF-RL]: Enhancing the Future of Teacher Practice via AI-enabled Formative Feedback for Job-Embedded Learning
协作研究 [FW-HTF-RL]:通过人工智能支持的工作嵌入学习形成性反馈增强教师实践的未来
  • 批准号:
    2326170
  • 财政年份:
    2023
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Standard Grant
RAPID: Longitudinal Modeling of Teams and Teamwork during the COVID-19 Crisis
RAPID:COVID-19 危机期间团队和团队合作的纵向建模
  • 批准号:
    2030599
  • 财政年份:
    2020
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Standard Grant
AI Institute: Institute for Student-AI Teaming
人工智能学院:学生人工智能团队学院
  • 批准号:
    2019805
  • 财政年份:
    2020
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Cooperative Agreement
Collaborative Research: FW-HTF-RM: Intelligent Facilitation for Teams of the Future via Longitudinal Sensing in Context
合作研究:FW-HTF-RM:通过上下文中的纵向感知为未来团队提供智能协助
  • 批准号:
    1928612
  • 财政年份:
    2019
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Standard Grant
AI-DCL: Collaborative Research: EAGER: Understanding and Alleviating Potential Biases in Large Scale Employee Selection Systems: The Case of Automated Video Interviews
AI-DCL:协作研究:EAGER:理解和减轻大规模员工选拔系统中的潜在偏见:自动视频面试的案例
  • 批准号:
    1921087
  • 财政年份:
    2019
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Standard Grant
Modeling Brain and Behavior to Uncover the Eye-Brain-Mind Link during Complex Learning
模拟大脑和行为以揭示复杂学习过程中的眼-脑-心联系
  • 批准号:
    1920510
  • 财政年份:
    2019
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Continuing Grant
EXP: Collaborative Research: Cyber-enabled Teacher Discourse Analytics to Empower Teacher Learning
EXP:协作研究:基于网络的教师话语分析,增强教师学习能力
  • 批准号:
    1735793
  • 财政年份:
    2017
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Standard Grant
Collaborative Research: Interpersonal Coordination and Coregulation during Collaborative Problem Solving
协作研究:协作解决问题过程中的人际协调和共同调节
  • 批准号:
    1660877
  • 财政年份:
    2017
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Continuing Grant
Collaborative Research: Interpersonal Coordination and Coregulation during Collaborative Problem Solving
协作研究:协作解决问题过程中的人际协调和共同调节
  • 批准号:
    1745442
  • 财政年份:
    2017
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Continuing Grant
EXP: Attention-Aware Cyberlearning to Detect and Combat Inattentiveness During Learning
EXP:注意力感知网络学习,用于检测和克服学习过程中的注意力不集中
  • 批准号:
    1748739
  • 财政年份:
    2017
  • 资助金额:
    $ 1.44万
  • 项目类别:
    Standard Grant

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