我喜欢哪些书？
Which books do I like?
AI总结：
本文提出 ISAAC 方法，通过 AI 智能体研究、标注用户评分书籍并推荐新书，支持读者认知文学偏好并寻找令人愉悦的书籍，实验证明其相较现有方法具有自动化与直觉整合及可解释推荐等优势。
摘要：
寻找令人愉悦的小说可能具有挑战性，部分原因在于故事具有多面性，且个人自身的文学品味可能难以确定。在此，我们引入了 ISAAC 方法（内省支持、AI 标注与策展），这是一个支持小说读者提升对其文学偏好的认知并寻找令人愉悦的书籍的流水线。ISAAC 包含四个步骤：用户提供书籍评分，AI 智能体研究并标注所提供的书籍，用户审查书籍享受中的模式，AI 智能体推荐新书。在这一概念验证自我研究中，作者测试了 ISAAC 是否能突显其书籍享受中的特有模式，激发对其文学品味的深度反思，并对令人愉悦的书籍和未充分探索的文学领域做出准确、个性化的推荐。结果突显了 ISAAC 相较于现有方法的显著优势，如自动化与直觉的整合、准确且可定制的标注，以及可解释的书籍推荐。观察到的缺点是，如果按表面价值采纳统计模式，ISAAC 的输出可能引发虚假的自我叙事；若在线文档匮乏，则无法对书籍进行标注；且阅读新手必须依赖假定的书籍评分或电影评分来驱动 ISAAC 流水线。我们讨论了 ISAAC 式书籍标注在文学趋势研究以及书籍与读者科学分类方面的额外机会。
英文摘要：
Finding enjoyable fiction books can be challenging, partly because stories are multi-faceted and one's own literary taste might be difficult to ascertain. Here, we introduce the ISAAC method (Introspection-Support, AI-Annotation, and Curation), a pipeline which supports fiction readers in gaining awareness of their literary preferences and finding enjoyable books. ISAAC consists of four steps: a user supplies book ratings, an AI agent researches and annotates the provided books, patterns in book enjoyment are reviewed by the user, and the AI agent recommends new books. In this proof-of-concept self-study, the authors test whether ISAAC can highlight idiosyncratic patterns in their book enjoyment, spark a deeper reflection about their literary tastes, and make accurate, personalized recommendations of enjoyable books and underexplored literary niches. Results highlight substantial advantages of ISAAC over existing methods such as an integration of automation and intuition, accurate and customizable annotations, and explainable book recommendations. Observed disadvantages are that ISAAC's outputs can elicit false self-narratives (if statistical patterns are taken at face value), that books cannot be annotated if their online documentation is lacking, and that people who are new to reading have to rely on assumed book ratings or movie ratings to power the ISAAC pipeline. We discuss additional opportunities of ISAAC-style book annotations for the study of literary trends, and the scientific classification of books and readers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
