Modeling Time, Space, and Networks for Effective and Efficient Information Retrieval

对时间、空间和网络进行建模以实现有效且高效的信息检索

• 批准号: RGPIN-2016-04138
• 负责人: Lin, Jimmy
• 金额: $ 3.93万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634449
• 关键词: Modeling; Time; Space; Networks; Effective

Citizens of modern societies are inundated with increasing quantities of information with no relief in sight. Search remains one of the best solutions today for combating this deluge. In today's mobile world, search systems need to understand time, space, and networks as they pertain to user needs: for example, we demand the most up-to-date facts, prefer nearby locations, and ask friends for help. Similarly, search systems need to model these important aspects of context: documents are created at specific times and locations, often with well-defined relationships to other documents (e.g., hyperlinks on the web, reply to a tweet).

现代社会的公民被越来越多的信息淹没，看不到缓解的迹象。搜索仍然是今天对抗这种洪水的最佳解决方案之一。在当今的移动的世界中，搜索系统需要了解时间、空间和网络，因为它们与用户需求有关：例如，我们需要最新的事实，更喜欢附近的位置，并向朋友寻求帮助。类似地，搜索系统需要对上下文的这些重要方面进行建模：文档是在特定的时间和位置创建的，通常与其他文档有明确的关系（例如，网络上的超链接，回复推特）。