Search engines are designed to create frameworks that locate records and data efficiently. The field of knowledge organization (KO) focuses on the categorization, arrangement, and representation of documents for retrieval, browsing, and related activities, whether performed by humans or machines [1]. In today's digital landscape, search engines such as Google dominate information retrieval. A key distinction between knowledge organization and information retrieval (IR) as research fields is that KO strives to represent information as structured by contemporary scholarship, whereas IR often relies on techniques like keyword matching, popularity metrics, or personalization algorithms [2]. The classification of records in KO typically mirrors the structure of knowledge in various scientific disciplines. For example, books on birds are categorized based on ornithological analysis [3]. Effective knowledge organization requires subject expertise, yet disagreements, particularly at the conceptual level, are common and often stem from conflicting paradigms [4]. Both retrieval technologies and knowledge organization systems are inevitably influenced by these paradigm conflicts, which serve as the foundation for the intersection of information retrieval and knowledge organization [5].

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