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References: Concept Taxonomies and Ontologies

  1. Taxonomy (general) - Wikipedia - Surveys classification and categorization practices across science, business, and computing beyond biology, the general sense of "taxonomy" this chapter narrows to classifying concepts in a learning graph.

  2. Ontology (information science) - Wikipedia - Explains ontologies as formal knowledge representations of concepts and their relationships, the more expressive structure this chapter contrasts with the flatter, single-category concept taxonomy used in this book.

  3. Cluster analysis - Wikipedia - Covers algorithms for grouping data points by similarity or connectivity, the technique this chapter's Clustering (Graph) section applies to automatically detect candidate taxonomy categories from graph structure.

  4. The Accidental Taxonomist (3rd Edition) - Heather Hedden - Information Today, Inc. - A widely used practitioner's guide to building and maintaining taxonomies and controlled vocabularies, covering category design, balance, and miscellaneous-bucket pitfalls central to this chapter.

  5. Semantic Web for the Working Ontologist (3rd Edition) - Dean Allemang, James Hendler, and Fabien Gandon - Morgan Kaufmann / ACM Books - A practical guide to building ontologies in RDF and OWL, illustrating how ontologies extend flat taxonomies with typed relationships beyond simple category membership.

  6. OWL 2 Web Ontology Language Document Overview - W3C - The official W3C introduction to OWL, the standard ontology language capable of expressing relationships like "is a type of" that go beyond this chapter's flat taxonomy-category model.

  7. Protégé - Stanford Center for Biomedical Informatics Research - The leading free, open-source ontology editor, used worldwide to build classification systems like the WHO's ICD-11, illustrating ontology and taxonomy construction in professional practice.

  8. Clustering in Machine Learning - GeeksforGeeks - Surveys centroid-, density-, and connectivity-based clustering algorithms, the automated grouping techniques this chapter's Clustering (Graph) section uses to detect densely connected node groups before abstraction names them.

  9. Taxonomies vs. Ontologies - Hedden Information Management - A taxonomy expert's explanation of how taxonomies and ontologies differ in origin, structure, and standards, directly supporting this chapter's distinction between a concept taxonomy and a full ontology.

  10. Connected Components in an Undirected Graph - GeeksforGeeks - A tutorial on finding densely connected node groups using DFS, BFS, and union-find, the algorithmic building block behind this chapter's graph-clustering approach to proposing taxonomy categories.