Workshop on Intelligent Systems for Information Exploration and Access (iSEA)

信息探索和访问智能系统研讨会（iSEA）

• 批准号: 2023924
• 负责人: Chirag Shah
• 金额: $ 2.38万
• 依托单位: University of Washington
• 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: 2020-04-01 至 2024-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2023924&HistoricalAwards=false
• 关键词: Workshop; Intelligent; Systems; Information; Exploration

We have made many advancements in the field of search and recommendation over the last few decades. However, there are still challenges and opportunities to address information access issues that involve solving tasks and accomplishing goals for a wide variety of users. Specifically, we lack intelligent systems that can detect not only the request a user is making (what), but also understand and utilize the intention (why) and strategies (how) while providing information. Many scholars in the fields of search, Recommender Systems, and AI have recognized the importance of extracting and understanding a user’s task and the intention behind doing that task in order to serve them better. However, we are still struggling to get out of single-query or single-turn interactions. The proliferation of intelligent agents that come integrated with smartphones and smart speakers has opened up new modality for interacting with information. But these agents will need to be able to work more intelligently in understanding the context and helping the users at the task level. Several events have taken place over the past few years around this topic, indicating continual and increased interest by scholars, but also highlighting the need for doing more.This two-day workshop in the Seattle area will bring together scholars, students, and leaders working or interested in this domain. The participants will be invited from different disciplines that include but not limited to search and AI. The workshop will have three primary goals: (1) learn and share about the current state of scholarship around intelligent systems for information access for solving tasks; (2) identify gaps in our knowledge and opportunities for developing new models, theories, and systems in this space; and (3) consolidate these discussions and insights to broader audiences through compilation of a report. The outcomes of this workshop will include a proceedings, a technical report, and a curriculum for teaching the topics covered through this workshop to undergraduate and graduate students.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.

过去几十年来，我们在搜索和推荐领域取得了许多进步，但是，解决涉及为各种用户解决任务和实现目标的信息访问问题仍然存在挑战和机遇。具体来说，我们缺乏智能。搜索、推荐系统和人工智能领域的许多学者已经认识到，系统不仅可以检测用户提出的请求（什么），还可以理解和利用用户的意图（原因）和策略（如何）。提取和理解用户任务的重要性然而，我们仍然在努力摆脱单查询或单轮交互，与智能手机和智能扬声器集成的智能代理的激增开辟了新的领域。但这些代理需要能够更智能地理解上下文并在任务级别帮助用户，过去几年围绕这一主题发生了几起事件，表明人们对这一主题的兴趣持续增加。学者们提出的建议，但同时也强调了采取行动的必要性这个在西雅图地区举行的为期两天的研讨会将邀请来自不同学科的学者、学生和领导者参加，其中包括但不限于搜索和人工智能领域。主要目标：（1）了解并分享有关解决任务的信息访问的智能系统的学术现状；（2）找出我们在该领域开发新模型、理论和系统的知识差距和机会； 3）通过编写报告将这些讨论和见解整合给更广泛的受众。本次研讨会的成果将包括会议记录、技术报告以及向本科生和研究生教授本次研讨会所涵盖主题的课程。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值进行评估，被认为值得支持以及更广泛的影响审查标准。