Probabilistic and link-based Methods for Exploiting Very Large Textual Repositories

用于利用超大型文本存储库的概率和基于链接的方法

• 批准号: 0329043
• 负责人: Dragomir Radev
• 金额: $ 31万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0329043&HistoricalAwards=false
• 关键词: Probabilistic; link; based; Methods; Exploiting

This research project addresses the disconnect between the way in which humans ask questions on the Web and the existing interfaces to the state-of-the-art search engines. Search engines require online searchers to formulate their requests in idiosyncratic query languages whose syntax is unnatural and hard to learn by typical users. Furthermore, existing search engines are notoriously bad at returning documents which do not contain any of the terms given by the user and yet which were retrieved as relevant to the user's information need. The proposed work focuses on two areas of research: (1) probabilistic question-to-query transformation (query modulation) for Web access and (2) models of content transfer over web links. The approach for (1) involves designing and evaluating algorithms and systems for automatic, rule-based conversion of natural language queries to the language of specific search engines. Part (2) facilitates retrieval of relevant Web documents by virtue of the links from other relevant documents to them. The expected outcomes and impact of this project are threefold: (1) a better understanding of the interaction between document retrieval and question-answering in a Web environment, (2) better models describing how document relevance is transferred over the Web hypergraph, and (3) better algorithms for natural language access to the Web which will make it easier for millions of web users to find information that they need in a timely, accurate, and intuitive way. All findings and artifacts developed under this grant will be widely disseminated and incorporate into a public-domain search engine, and the results will be accessible via the project Web site (http://tangra.si.umich.edu/clair).

这个研究项目解决了人类在网络上提问的方式与现有的最先进的搜索引擎接口之间的脱节。搜索引擎要求在线搜索者用特殊的查询语言来表达他们的请求，这些语言的语法不自然，并且很难被普通用户学习。此外，现有的搜索引擎在返回不包含用户给出的任何术语但被检索为与用户的信息需求相关的文档方面是出了名的差。拟议的工作集中在两个领域的研究：（1）概率问题查询转换（查询调制）的Web访问和（2）模型的内容传输的Web链接。（1）的方法涉及设计和评估用于将自然语言查询自动地、基于规则地转换为特定搜索引擎的语言的算法和系统。第（2）部分通过从其他相关文档到相关Web文档的链接，方便检索相关Web文档。该项目的预期成果和影响有三个方面：（1）更好地理解Web环境中文档检索和问答之间的交互，（2）更好地描述文档相关性如何通过Web超图传递的模型，以及（3）更好的自然语言访问网络的算法，这将使数以百万计的网络用户更容易找到他们需要的信息，及时、准确和直观的方式。在该赠款下开发的所有研究结果和人工制品将广泛传播，并纳入公共领域搜索引擎，其结果将通过项目网站（http：//tangra.si.umich.edu/clair）访问。