Enhanced Digital Libraries Through Recommendation: Exploring the Use of Citations, Personal Bibliographies, and Metadata to Synthesize Library Services for Individuals

本提案探讨了使用推荐系统技术，将个人引导到大型馆藏的一部分，作为帮助图书馆用户和图书管理员的工具。提出的研究是建立在研究表明推荐可以有效地帮助研究人员找到与现有文档相关的额外引用的特定任务的基础上的。应用程序将在设计新的图书馆服务的三组关键研究问题的背景下进行研究：(1)关于文章元数据的问题，即关于作者、引用、地点和其他相关信息的有价值的信息，以及如何挖掘元数据以更好地指导图书馆用户。(2)关于针对不同信息需求的推荐算法的问题，特别关注跨元数据类型的算法（例如，从引文中查找人或从分类数据中查找引文），以及可以被图书馆管理员和其他高级用户使用的模块化算法工具包的设计，以合成新的推荐类型。(3)关于用户界面的问题，需要使这些工具对各种不同的用户（从学生到经验丰富的图书馆员）都能访问和有效。最后，本研究将对数位图书馆、推荐系统、人机交互等研究领域做出新的贡献。

This proposal explores the use of recommender systems technology for guidingindividuals to parts of a large collection as a tool to help library users and librarians alike. Theproposed research is built upon research showing that recommenders can be effective for helpingresearchers with the specific task of finding additional citations germane to an existing document.Applications will be studied in the context of three key sets of research questions about the designof new library services: (1) Questions about article metadata the valuable information about authors,citations, venues, and other related information and how metadata can be mined to better guide libraryusers. (2) Questions about recommender algorithms for a diverse set of information needs, with particularinterest in algorithms that cross metadata types (e.g., finding people from citations or finding citationsfrom taxonomy data) and on the design of a modular toolkit of algorithms that can be used by librariansand other power users to synthesize new recommendation types. (3) Questions about the user interfacesneeded to make such tools accessible to and effective for a variety of different users, from students toexperienced librarians. In the end, the research will make novel contributions to the field of digitallibraries and the research areas of recommender systems and human-computer interaction.