CRI: CRD - Supporting User Data, Privacy, and Evaluation in the Lemur Toolkit

CRI：CRD - 在 Lemur 工具包中支持用户数据、隐私和评估

• 批准号: 0707801
• 负责人: W. Bruce Croft
• 金额: --
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0707801&HistoricalAwards=false
• 关键词: CRI; CRD; Supporting; User; Data

The Lemur Toolkit (http://www.lemurproject.org) has become a standard resource for researchers in the field of information retrieval. The combination of very efficient indexing tools, support for a variety of retrieval models, and a powerful query language has enabled a wide variety of research projects. In this collaborative project, W. Bruce Croft, University of Massachusetts - Amherst and Jamie Callan, Carnegie Mellon University are extending the toolkit with new features, search techniques, efficiency improvements, and evaluation measures to broaden the range of research it can support and to keep up-to-date with the latest research. One feature in particular is a toolbar for the acquisition and analysis of user data, such as clickthrough, that is the basis for improving many Web search techniques. This new feature helps the academic community study these techniques and will include explicit controls for safeguarding the privacy of the data and anonymizing subsets for research. The toolkit is already in use in educational and research environments world-wide and the extensions are likely to support new research leading to more effective search engines. This in turn will have a significant impact on Web users by improving the quality of retrieved results.

Lemur Toolkit（www.lemurproject.org）已成为信息检索领域研究人员的标准资源。非常高效的索引工具、对各种检索模型的支持以及强大的查询语言的结合，使各种各样的研究项目成为可能。在这个合作项目中，W。马萨诸塞州阿默斯特大学的布鲁斯克罗夫特和卡内基梅隆大学的杰米·卡兰正在用新的功能、搜索技术、效率改进和评估措施来扩展工具包，以扩大它可以支持的研究范围，并与最新的研究保持同步。一个特别的功能是用于获取和分析用户数据的工具栏，例如点击，这是改进许多Web搜索技术的基础。这一新功能有助于学术界研究这些技术，并将包括明确的控制措施，以保护数据的隐私和匿名化研究子集。该工具包已在世界各地的教育和研究环境中使用，其扩展可能会支持新的研究，从而导致更有效的搜索引擎。这反过来将通过提高检索结果的质量对网络用户产生重大影响。