Kategorilestirme

Kategorilestirme is the process of organizing items by assigning them to categories based on shared characteristics. It aims to facilitate storage, retrieval, analysis, and use of information or resources. The practice is common in information management, libraries, archives, e-commerce, digital media, and data science. It can be performed manually by people, automated by software, or by a combination of both.

A typical approach is to define a taxonomy or controlled vocabulary, create a set of categories (and subcategories), and apply them consistently. Methods include rule-based classification, supervised learning with labeled data, unsupervised clustering, and hybrid strategies. Categories may be hierarchical, flat, or faceted, and are often supported by metadata and tagging.

Benefits include improved search and filtering, easier navigation, better data governance and interoperability, and scalable management of large collections. Categorilestirme also supports analytics, reporting, and personalized recommendations.

Challenges include subjectivity and ambiguity, overlapping categories, category proliferation, cultural or language differences, and ongoing maintenance costs. Best practices emphasize a clearly defined scope, non-overlapping labels, stable naming, governance, and periodic reviews. Related concepts include taxonomy, ontology, controlled vocabulary, tagging, metadata, and automatic classification.