SBIR Phase I: Cross-language Information Retrieval Using Deep Syntax Parsing

SBIR 第一阶段：使用深度语法分析进行跨语言信息检索

• 批准号: 0233050
• 负责人: Konstantin Bogatyrev
• 金额: $ 10万
• 依托单位: Universal Dialog, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-01-01 至 2003-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0233050&HistoricalAwards=false
• 关键词: SBIR; Phase; Cross; language; Information

This Small Business Innovation Research (SBIR) Phase I project addresses the construction of a cross-lingual retrieval system based on deep linguistic analysis intended to deliver efficiencies and cost savings and reduce communication barriers worldwide. By 2003, 70 percent of the estimated 1.3 billion users of the Internet will be non-English speaking. Thus the need to enable automated, reliable accessibility to information in more than one language is clear. Most existing information retrieval systems are either monolingual or cross-language with limited success and no translation capabilities. The investigator's Cross-Language Information Retrieval System (CLIR) will produce significant performance increases in the recall and precision of a cross-language sear. The investigative team will encapsulate cutting edge natural language processing (NLP) technology developed on a consistent theoretical foundation into a modular and scalable application-programming interface. The system will incorporate an extraction component for the matching of relevant lexemes based on their syntactic context, and a probabilistic module, which will disambiguate multiple interpretation based on expectation. The firm has secured an exclusive license from Russian Academy of Sciences for the use of complex NLP algorithms that will be integrated into the CLIR technology, creating a state-of-the-art linguistic kernel.Universal Dialog proffered technology will provide any person, business, organization or government, as well as any software that integrates their Cross-Language Information Retrieval, a faster, less costly solution for the retrieval of multilingual information, with a higher degree of precision, recall and scalability that CLIR methods currently available. The firm plans to integrate the technology to be developed in this project into its Cross-Language Communication Platform (CLCP). CLCP will enable users to retrieve, summarize, and fully translate retrieved data.

这个小型企业创新研究（SBIR）第一阶段项目旨在构建一个基于深度语言分析的跨语言检索系统，旨在提高效率和节省成本，并减少全球范围内的沟通障碍。 到2003年，估计13亿互联网用户中的70%将是非英语用户。 因此，显然需要以一种以上的语文自动可靠地获取信息。 大多数现有的信息检索系统要么是单语言的，要么是跨语言的，成功有限，没有翻译功能。 研究者的跨语言信息检索系统（CLIR）将在跨语言搜索的召回率和准确率方面产生显著的性能提高。 研究团队将在一致的理论基础上开发的尖端自然语言处理（NLP）技术封装到模块化和可扩展的应用程序编程接口中。该系统将包括一个提取组件，用于根据句法上下文匹配相关词汇，以及一个概率模块，该模块将根据预期消除多种解释的歧义。 该公司已获得俄罗斯科学院的独家许可，使用复杂的NLP算法，将集成到CLIR技术中，创建一个最先进的语言内核。Universal Dialog提供的技术将为任何个人，企业，组织或政府以及任何集成跨语言信息检索的软件提供更快，成本更低的多语言信息检索解决方案，具有更高的精度，召回率和可扩展性，CLIR方法目前可用。 该公司计划将该项目中开发的技术集成到其跨语言通信平台（CLCP）中。 CLCP将使用户能够检索、总结和完全翻译检索到的数据。