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.

在过去的几十年里，我们在搜索和推荐领域取得了许多进步。然而，仍然有挑战和机遇，以解决信息访问问题，涉及解决任务和实现目标，为各种各样的用户。具体来说，我们缺乏智能系统，不仅可以检测用户的请求（什么），还可以在提供信息时理解和利用意图（为什么）和策略（如何）。搜索、推荐系统和人工智能领域的许多学者已经认识到提取和理解用户的任务以及执行该任务背后的意图的重要性，以便更好地为他们服务。然而，我们仍然在努力摆脱单次查询或单轮交互。与智能手机和智能扬声器集成的智能代理的激增开辟了与信息交互的新模式。但是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。在过去的几年里，围绕这一主题举办了几次活动，表明学者们对这一主题的兴趣不断增加，但也强调了做更多工作的必要性。这次为期两天的研讨会将在西雅图地区举行，与会者包括学者、学生和对这一领域感兴趣的领导人。参与者将被邀请来自不同的学科，包括但不限于搜索和人工智能。研讨会将有三个主要目标：（1）学习和分享围绕智能系统的奖学金现状，用于解决任务的信息访问;（2）确定我们在知识和机会方面的差距，以开发新的模型，理论和系统在这一领域;（3）通过编写报告，将这些讨论和见解整合到更广泛的受众中。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讲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知识价值和更广泛的影响审查标准进行评估，被认为值得支持。