ITR: From Bits to Information: Statistical Learning Technologies for Digital Information Management and Search

ITR：从比特到信息：数字信息管理和搜索的统计学习技术

• 批准号: 0085836
• 负责人: Tomaso Poggio
• 金额: $ 204万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-09-01 至 2004-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0085836&HistoricalAwards=false
• 关键词: ITR; Bits; Information; Statistical; Learning

Modern statistical learning approaches are expected to play a key role in providing more powerful tools to harvest information from bits, a crucial and growing problem for the Internet. The goal of this project is thus to develop a new technology for the management, organization, and search of multimedia digital information by exploiting and extending new statistical learning theories and algorithms. In the process we expect to prototype key system components and to develop scientific insights. Anticipated outcomes of the research are (1) new learning algorithms and associated representations that can be applied to categorize text, images, and video, (2) new theoretical analyses of these learning algorithms and query-answering methods and (3) demonstrations and evaluations of prototype systems for classifying and routing email messages and searching, categorizing, and extracting information on the Web.Smarter classification software for multimedia data is a prerequisite to enable a second, more intelligent wave of Internet technologies. Automatic techniques to route, organize and search information are needed to help individuals and organizations exploit the sea of data that the computer networks are creating. The success of projects like this will make such a step possible and accelerate the evolution of the Internet.

现代统计学习方法预计将发挥关键作用，提供更强大的工具，从比特中获取信息，这是互联网的一个关键和日益严重的问题。因此，本项目的目标是通过开发和扩展新的统计学习理论和算法，开发一种用于多媒体数字信息的管理、组织和搜索的新技术。在这个过程中，我们希望原型的关键系统组件，并制定科学的见解。研究的预期成果是（1）新的学习算法和相关的表示，可应用于分类文本，图像和视频，（2）这些学习算法和问答方法的新理论分析和（3）示范和评估原型系统分类和路由电子邮件消息和搜索，分类，更智能的多媒体数据分类软件是实现第二次更智能的互联网技术浪潮的先决条件。路由、组织和搜索信息的自动化技术需要帮助个人和组织利用计算机网络产生的海量数据。像这样的项目的成功将使这一步成为可能，并加速互联网的发展。