CAREER: Future of Search: User, Social Networks and Language

职业：搜索的未来：用户、社交网络和语言

• 批准号: 0953908
• 负责人: Yi Zhang
• 金额: $ 50.47万
• 依托单位: University of California-Santa Cruz
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0953908&HistoricalAwards=false
• 关键词: CAREER; Future; Search; User; Social

How to retrieve relevant information for a specific user under a specific set of circumstances is a challenging research problem. The goal of this research project is to tackle this challenge and lay the foundation for the next generation of search engines. Instead of simply matching a query to documents that contain query words, the approach developed here is a unified user-centric retrieval framework that consists of: (1) personalization: learning a user model that takes into consideration the content, context and decision criteria of a user; (2) language processing: learning better text representation for retrieval from heterogeneous corpus and linguistic resources; and (3) social networks: further improving the user model based on social norms and a user's social networks. To evaluate the framework, a personalized social search engine will be developed. The result of this project will be a unified retrieval framework with a set of novel techniques applicable across a wide range of information retrieval (IR) tasks, including: search engines, recommender systems and adaptive filtering systems. Through the PI's industry collaboration, the results of this project are expected to be incorporated in commercial systems, and thus benefit millions of users. K-12 students, undergraduate, graduate students, and engineers in Silicon Valley will be involved and benefit from the project. The project will lead to research-based educational materials (lecture slides, video lectures, book chapters and course projects). Project results, including publications, open source software, annotated data sets, demos and course materials, will be disseminated via the project website (http://www.soe.ucsc.edu/~yiz/futureofsearch).

如何在一组特定情况下为特定用户检索相关信息是一个具有挑战性的研究问题。该研究项目的目的是应对这一挑战，并为下一代搜索引擎奠定基础。这里开发的方法不简单地将查询与包含查询单词的文档匹配，而是一个以用户为中心的统一检索框架，该框架由：（1）个性化：学习一个用户的用户模型，以考虑用户的内容，上下文和决策标准； （2）语言处理：从异质语料库和语言资源中学习更好的文本表示； （3）社交网络：基于社交规范和用户的社交网络进一步改善用户模型。 为了评估框架，将开发一个个性化的社交搜索引擎。该项目的结果将是一个统一的检索框架，该框架具有一组适用于广泛信息检索（IR）任务的新型技术，包括：搜索引擎，建议系统和自适应过滤系统。 通过PI的行业合作，预计该项目的结果将纳入商业系统，从而使数百万用户受益。 K-12学生，本科生，研究生和硅谷的工程师将参与并从该项目中受益。该项目将导致基于研究的教育材料（演讲幻灯片，视频讲座，书籍章节和课程项目）。项目结果，包括出版物，开源软件，注释数据集，演示和课程材料，将通过项目网站（http://www.soe.ucsc.edu/~yiz/futureofsearch）进行传播。