Providing effective access paths to content is a key task in digital libraries. Oftentimes, such access paths are realized through advanced query languages, which, on the one hand, users may find challenging to learn or use, and on the other, requires libraries to convert their content into a high quality structured representation. As a remedy, narrative information access proposes to query library content through structured patterns directly, to ensure validity and coherence of information. However, users still find it challenging to express their information needs in such patterns. Therefore, this work bridges the gap by introducing a method that deduces patterns from keyword searches. Moreover, our user studies with participants from the biomedical domain show their acceptance of our system.

翻译：为内容提供有效访问路径是数字图书馆的核心任务。这些访问路径通常通过高级查询语言实现，但一方面用户可能觉得这类语言难以学习或使用，另一方面图书馆需要将内容转换为高质量的结构化表示。作为解决方案，叙事信息访问提出直接通过结构化模式查询图书馆内容，以确保信息的有效性和连贯性。然而，用户仍难以通过此类模式清晰表达信息需求。为此，本研究提出了一种从关键词搜索中推导模式的方法，弥合了这一鸿沟。此外，我们针对生物医学领域参与者开展的用户研究表明，该系统的用户接受度良好。