conceptmodification

Concept modification is the process of adjusting the definition, scope, or relationships of a concept in response to new information, evidence, or changing goals. The aim is to improve the usefulness and accuracy of concepts used in reasoning, communication, and decision-making. In cognitive science, it refers to updating mental categories through changes to prototype structures, feature weights, or category boundaries. In information science and knowledge management, concept modification often involves revising ontologies or taxonomies to reflect new domain knowledge or user needs.

Practices involve data-driven analysis, theory revision, or stakeholder negotiation. Typical mechanisms include redefining the criteria that determine category membership, expanding or shrinking the set of exemplars, or altering the logical relationships between concepts (such as parent-child or part-whole links). Techniques from machine learning and ontology engineering, such as incremental ontology evolution or active learning, exemplify algorithmic concept modification.

Examples include reclassifying a biological organism when genetic evidence prompts a new genus, redefining color categories in vision science, or updating a product taxonomy after adding new features. In research and industry, concept modification supports adaptation to new evidence, technologies, or user requirements, while preserving coherence in knowledge structures.

History and theory frame concept modification as part of broader discussions on theory change, schema evolution, and knowledge representation. Critics caution that frequent modification can cause instability or interoperability problems if governance and documentation are lacking. Related topics include concept change, taxonomy, ontology engineering, and schema evolution.