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:在数字图书馆中,提供有效的内容访问路径是一项关键任务。通常,这些访问路径是通过高级查询语言来实现的,一方面,用户可能会发现学习或使用这些语言较为困难,另一方面,则需要图书馆将其内容转换为高质量的结构化表示形式。作为一种解决方案,叙事信息访问旨在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一致性。然而,用户仍然难以用这种模式表达其信息需求。因此,本研究引入了一种通过关键字搜索推断出模式的方法。此外,我们针对来自生物医学领域的参与者进行了用户研究,结果表明他们接受我们的系统。