Improving Information Retrieval with Machine Learning

通过机器学习改进信息检索

• 批准号: 46392-2012
• 负责人: Ling, Charles
• 金额: $ 2.48万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=545012
• 关键词: Improving; Information; Retrieval; Machine; Learning

Information retrieval (IR) systems including various search engines have played important roles in our life. They include general web search engines (such as Google), vertical search engines (such as product search in Amazon.com), specific media search (such as image search), and so on. In the past years I have made fruitful and significant contributions in several important areas of machine learning. The objectives of this research program are to expand my research in machine learning, and leverage it to improve the performance and user experience of IR systems for people to easily obtain highly accurate and useful information.

包括各种搜索引擎在内的信息检索系统在人们的生活中扮演着重要的角色。这些搜索引擎包括通用网络搜索引擎（如Google）、垂直搜索引擎（如Amazon.com中的产品搜索）、特定媒体搜索（如图像搜索）等等。在过去的几年里，我在机器学习的几个重要领域做出了卓有成效的重大贡献。这个研究项目的目标是扩大我在机器学习方面的研究，并利用它来改善IR系统的性能和用户体验，让人们轻松获得高度准确和有用的信息。