OAC Core: Small: Collaborative Research: Conversational Agents for Supporting Sustainable Implementation and Systemic Diffusion of Cyberinfrastructure and Science Gateways

OAC 核心：小型：协作研究：支持网络基础设施和科学网关可持续实施和系统扩散的对话代理

• 批准号: 2007100
• 负责人: Kerk Kee
• 金额: $ 20万
• 依托单位: Texas Tech University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2007100&HistoricalAwards=false
• 关键词: OAC; Core; Small; Collaborative; Research

By designing a chatbot that harnesses the power of machine learning to connect scientists/educators with existing tools, datasets, and other experts, this sociotechnical project aims to remove significant user support barriers in the US STEM community. A chatbot called Vidura will be developed to provide personalized user support to novice and expert users in the form of a conversational agent to facilitate interdisciplinary research and education collaborations. The chatbot investigations in the project benefit the investments in science gateways (SG) and cyberinfrastructure (CI) made by the NSF and other federal agencies for over two decades. Vidura chatbot works around the clock and makes the greatest impacts when user support by human agents (i.e., domain specialists or CI support persons) is not available and/or is too costly as a science gateway surges in user uptake. The Vidura chatbot will initially be prototyped in CyNeuro, a neuroscience SG, but will be made accessible to be adapted in SGs across multiple domains to benefit the broader research/education communities.This project integrates human communication science, conversational agent design, recommender algorithms, machine learning techniques, domain topic modeling in a synergistic way that advances social science, computer science, and neuroscience. In addition, this sociotechnical project provides research opportunities to benefit undergraduate and graduate students in both social and computer sciences and creates new interdisciplinary courses. The project activities will benefit students with diverse backgrounds as it will be carried out at two large public universities, one of which is a Hispanic serving institution. The project objectives and activities will focus on answering three main research questions: (i) How to design a chatbot for gathering user requirements and creating user profiles with proficiency in order to provide personalized expert service support and maintain adoption? (ii) How to equip the chatbot communication and custom dialogue flows during support actions with underlying recommender algorithms using un-supervised machine learning within/across science domains? (iii) How to implement a chatbot framework in research and education workflows of data-intensive/computation-intensive application communities (such as the neuroscience community, as well as in CI provider communities of SGCI, XSEDE, NSG, CyVerse, and JetStream) to evaluate utility across domains and identify best practices for ongoing relevance? The project findings will ultimately advance knowledge on how to enable conversational agents implemented as chatbot interfaces with pertinent underlying recommender algorithms in order to provide expert services to scientific domain users with reduced cost and increased convenience.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

通过设计聊天机器人，该聊天机器人利用机器学习的力量将科学家/教育者与现有工具，数据集和其他专家联系起来，该社会技术项目旨在消除美国STEM社区的重要用户支持障碍。将开发一个名为Vidura的聊天机器人，以以对话代理的形式向新手和专家用户提供个性化的用户支持，以促进跨学科的研究和教育合作。该项目的聊天机器人调查使NSF和其他联邦机构对科学网关（SG）（SG）和网络基础设施（CI）的投资有益于二十年多。 Vidura Chatbot可以全天候工作，当人类代理商（即域专家或CI支持人员）的用户支持不可用时和/或作为用户吸收中的科学网关激增时，会产生最大的影响。 The Vidura chatbot will initially be prototyped in CyNeuro, a neuroscience SG, but will be made accessible to be adapted in SGs across multiple domains to benefit the broader research/education communities.This project integrates human communication science, conversational agent design, recommender algorithms, machine learning techniques, domain topic modeling in a synergistic way that advances social science, computer science, and neuroscience.此外，该社会技术项目还提供了研究机会，使社会和计算机科学领域的本科生和研究生受益，并创建新的跨学科课程。项目活动将使具有不同背景的学生受益，因为这将在两所大型公立大学进行，其中一所是西班牙裔服务机构。项目目标和活动将重点放在回答三个主要研究问题上：（i）如何设计聊天机器人来收集用户需求并熟练地创建用户配置文件，以提供个性化的专家服务支持并维护采用？ （ii）如何使用科学领域内/跨科学的机器学习在支持动作的过程中配备聊天机器人的通信和自定义对话流？ （iii）如何在数据密集/计算密集型应用程序社区（例如神经科学社区以及SGCI，XSEDE，NSG，NSG，CYVERSE和JETSTREAM的CI提供者社区）中实施聊天机器人框架（例如神经科学界以及CI提供者社区），以评估跨域和跨域和最佳实践的最佳实践？该项目的发现最终将促进有关如何启用作为聊天机器人实施的对话剂与基本推荐算法互动的知识，以便为科学领域使用者提供专家服务，以降低成本和增加的便利性。这一奖项反映了NSF的立法任务，并被认为是通过基金会的智力上的评估来进行评估，并获得了基础的智力效果。

项目成果

Measurement of Utility in User Access of COVID-19 Literature via AI-powered Chatbot

通过 AI 驱动的聊天机器人测量用户访问 COVID-19 文献的效用

• DOI: 10.1109/aipr52630.2021.9762160
• 发表时间: 2021
• 期刊: IEEE AIPR
• 作者: Oruche, Roland;Milman, Eric D.;Cheng, Xiyao;Joish, Megha;Kulkarni, Chaitra;Sharma, Agrim;Kee, Kerk;Regunath, Hariharan;Calyam, Prasad
• 通讯作者: Calyam, Prasad