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

狐猴工具包(http://www.lemurproject.org))已经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相结合，使各种各样的研究项目成为可能。在这个合作项目中，马萨诸塞大学阿默斯特分校的W.Bruce Croft和卡内基梅隆大学的Jamie Callan正在扩展工具包，添加新功能、搜索技术、效率改进和评估措施，以扩大其可以支持的研究范围，并与最新研究保持同步。一个特别的功能是用于获取和分析用户数据的工具栏，例如点击链接法，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，并将包括保护数据隐私和匿名研究子集的明确控制。该工具包已经在世界各地的教育和研究环境中使用，这些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Web用户产生重大影响。

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.