Taxonomies provide hierarchical categorization and classification of not only content, but also products and brands represented in online directories and product catalogs.
A controlled vocabulary is a way to insert an interpretive layer of semantics between the terms entered by the user and the underlying database to better represent the original intention of the user’s terms. The most effective communication occurs when all parties involved agree on the meaning of the terms being used. Consequently, finding the right words to communicate the message of your website can be one of the most difficult parts of developing it.
How would this apply in the world of healthcare?
With patient electronic medical records (EMRs), accessing information for insurance coding and research depends on standardized taxonomies to organize and index the content. Controlled vocabularies are necessary to interpret content consistently.
A controlled vocabulary is needed to ensure that machine-assisted or fully-automated indexing is comprehensive, regardless of what you are indexing. Indexing systems can streamline the categorization process for greater efficiency and accuracy by using Bayesian engines or rule-based approaches. The accuracy of medical indexing systems varies widely, based on the degree of automation and capacity for semantic analysis.
How content is classified impacts its findability. True findability can only be achieved when you index against a solid, standards-based taxonomy. Professionals should look for a group experienced in taxonomy creation to ensure findability and accuracy in machine-assisted indexing.
Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies and associated rule bases for machine-assisted indexing.
Data Harmony is a fully customizable suite of software products designed to maximize precise, efficient information management and retrieval. Our suite includes tools for taxonomy and thesaurus construction, machine aided indexing, database management, information retrieval and explainable AI.
Explainable AI is used to describe an AI model, its expected impact and potential biases. Why is this important? Because the results can have an impact on data security or patient safety.
Melody K. Smith
Sponsored by Access Innovations, changing search to found.
