ACM Recommender Systems Conference 2011 Doctoral Symposium

ACM 推荐系统大会 2011 博士生研讨会

基本信息

  • 批准号:
    1144050
  • 负责人:
  • 金额:
    $ 0.98万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2011
  • 资助国家:
    美国
  • 起止时间:
    2011-09-01 至 2012-08-31
  • 项目状态:
    已结题

项目摘要

This is funding to support travel for a diverse group of US PhD students and distinguished faculty mentors to participate in an international doctoral consortium on research on recommender systems that will be co-located with the 2011 ACM Conference on Recommender Systems (ACM RecSys) in Chicago, Illinois. RecSys is a leading forum that brings together faculty, students, research staff, and industry researchers who share an interest in advancing the science of recommender systems, both in terms of the underlying algorithms that predict choices based on a variety of data (e.g., ratings, social links, context) and in terms of the human elements of the process such as eliciting ratings or presenting recommendations to users. The main goal of this Doctoral Colloquium is to help train the next generation of researchers in this area.The 2011 RecSys Doctoral Consortium will provide a group of approximately 6 PhD students studying recommender systems with an environment in which they can share and discuss their goals, methods and results at an early stage of their research. It will take place on October 23, 2011, the first day of the conference. By participating in the doctoral consortium, students will gain feedback on their work from other students and six prominent faculty members, allowing them to enhance their own research proposal. Students will also develop a better understanding of the different research communities engaged in the study of recommender systems, and learn how to position their own work within this community. In addition, the consortium will provide students with opportunities to make new professional connections beyond their own disciplines. Students will be recruited for the doctoral consortium through advertisement on the conference website, postings to relevant mailing lists and direct solicitation to faculty working in the area of information science and related fields. Particular attention will be placed on identifying participants from under-represented groups. To apply for the consortium, students will submit an extended abstract outlining their research goals and work to date, a curriculum vita, a paragraph describing what they expect to get from participating in the doctoral consortium, and a letter of reference from their primary advisor. Applications will be rated by the consortium chairs in terms of originality, importance of research topic, intellectual and methodological rigor, stage of work, and advisor recommendation. Priority will be given to students who have formulated their dissertation topic but are early enough in the process that they can still benefit from feedback. Broader impacts: The RecSys doctoral consortia traditionally bring together the best of the next generation of researchers in recommender systems and related areas, allowing them to create a social network both among themselves and with senior researchers at a critical stage in their professional development. Participation is encouraged from a broad range of relevant disciplines and approaches, thereby broadening attendees' perspectives on their topics of study and promoting advancement of the field. The organizers will try explicitly to identify and include the broadest possible group of highly qualified participants. As a consequence of these steps, the student and faculty participants will constitute a diverse group across a variety of dimensions, which will help broaden the students' horizons to the future benefit of the field and to U.S. e-commerce, which relies heavily on recommender systems.
这笔资金将用于资助一群不同的美国博士生和杰出的教师导师参加一个关于推荐系统研究的国际博士联盟,该联盟将与2011年在伊利诺伊州芝加哥举行的ACM推荐系统会议(ACM RecSys)共同举办。RecSys是一个领先的论坛,汇集了教职员工、学生、研究人员和行业研究人员,他们对推进推荐系统的科学感兴趣,无论是基于各种数据(例如,评分、社会链接、上下文)预测选择的底层算法,还是基于过程中的人为因素(例如,获得评分或向用户呈现推荐)。本次博士研讨会的主要目标是帮助培养该领域的下一代研究人员。2011年RecSys博士联盟将为大约6名研究推荐系统的博士生提供一个环境,在这个环境中,他们可以在研究的早期阶段分享和讨论他们的目标、方法和结果。它将于2011年10月23日,即会议的第一天举行。通过参与博士联盟,学生将获得其他学生和六位杰出教师对他们工作的反馈,使他们能够加强自己的研究计划。学生还将更好地了解从事推荐系统研究的不同研究团体,并学习如何在这个团体中定位自己的工作。此外,该联盟将为学生提供在自己学科之外建立新的专业联系的机会。将通过在会议网站上发布广告、在相关邮件列表中发帖和直接向信息科学及相关领域的教职员工征集博士生。将特别注意确定代表人数不足的群体的参加者。为了申请该联盟,学生将提交一份扩展摘要,概述他们的研究目标和迄今为止的工作,一份个人简历,一段描述他们希望从参与博士联盟中得到什么的段落,以及他们的主要导师的推荐信。申请将由联盟主席根据原创性,研究课题的重要性,知识和方法的严谨性,工作阶段和顾问推荐进行评级。优先考虑那些已经制定了论文主题的学生,但在这个过程中足够早,他们仍然可以从反馈中受益。更广泛的影响:传统上,RecSys博士联盟将推荐系统和相关领域的下一代最好的研究人员聚集在一起,使他们能够在自己之间以及与处于专业发展关键阶段的高级研究人员建立一个社会网络。鼓励来自广泛的相关学科和方法的参与,从而拓宽与会者对其研究主题的看法,促进该领域的进步。组织者将明确地确定并包括尽可能广泛的高素质参与者群体。作为这些步骤的结果,学生和教师参与者将在各个方面组成一个多样化的群体,这将有助于拓宽学生的视野,使其受益于该领域和严重依赖推荐系统的美国电子商务。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Alexander Tuzhilin其他文献

Recommendation opportunities: improving item prediction using weighted percentile methods in collaborative filtering systems
推荐机会:在协同过滤系统中使用加权百分位数方法改进项目预测
Recommending Items with Conditions Enhancing User Experiences Based on Sentiment Analysis of Reviews
基于评论情感分析推荐符合条件的物品以增强用户体验
  • DOI:
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Konstantin Bauman;B. Liu;Alexander Tuzhilin
  • 通讯作者:
    Alexander Tuzhilin
Providing information system support for simulations using the Cassandra+ system
  • DOI:
    10.1023/a:1018996221025
  • 发表时间:
    1997-01-01
  • 期刊:
  • 影响因子:
    4.500
  • 作者:
    P. Balasubramanian;Alexander Tuzhilin
  • 通讯作者:
    Alexander Tuzhilin
Knowledge management revisited
重新审视知识管理
Towards the Next Generation of Recommender Systems
  • DOI:
    10.2991/icebi.2010.28
  • 发表时间:
    2010-12
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Alexander Tuzhilin
  • 通讯作者:
    Alexander Tuzhilin

Alexander Tuzhilin的其他文献

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{{ truncateString('Alexander Tuzhilin', 18)}}的其他基金

EAGER: Collaborative Research: Sequential Recommender Systems in Mobile and Pervasive Environments
EAGER:协作研究:移动和普及环境中的顺序推荐系统
  • 批准号:
    1256036
  • 财政年份:
    2012
  • 资助金额:
    $ 0.98万
  • 项目类别:
    Standard Grant
Knowledge Discovery in Temporal Databases
时态数据库中的知识发现
  • 批准号:
    9318773
  • 财政年份:
    1994
  • 资助金额:
    $ 0.98万
  • 项目类别:
    Continuing Grant

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CAREER: User-Based Simulation Methods for Quantifying Sources of Error and Bias in Recommender Systems
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NSF Student Travel Grant for 2022 ACM Recommender Systems Conference
2022 年 ACM 推荐系统会议 NSF 学生旅行补助金
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