In today’s data-driven world, managing vast amounts of information efficiently is paramount. Businesses, researchers and organizations rely on structured taxonomies to organize, classify and retrieve data effectively. Taxonomies provide a systematic way to categorize information, enabling easier navigation and analysis. However, as data continues to grow exponentially, traditional manual approaches to taxonomy creation and maintenance struggle to keep pace. This is where artificial intelligence (AI) steps in, offering innovative solutions to enhance and automate the creation and management of custom taxonomies.

In various domains such as e-commerce, content management and scientific research, taxonomies serve as the backbone for organizing information. For instance, in e-commerce, a well-structured taxonomy can simplify product navigation for customers, leading to increased sales and customer satisfaction. Similarly, in scientific research, taxonomies facilitate the organization of vast amounts of data, making it easier for researchers to identify trends, patterns and relationships.

Traditionally, creating and maintaining taxonomies have been labor-intensive tasks requiring domain expertise and significant time investment. Subject matter experts painstakingly categorize and label data, often resulting in inconsistencies, biases and limited scalability. Moreover, as data sources multiply and evolve, manual taxonomies struggle to adapt quickly, leading to outdated and inefficient classification systems.

AI technologies, including machine learning, natural language processing (NLP), and knowledge graphs, offer transformative capabilities for custom taxonomy creation and management. By leveraging AI, organizations can streamline the taxonomy development process, improve accuracy and scale efficiently.

AI-driven knowledge graphs provide a powerful framework for representing interconnected concepts and entities within a domain. By integrating taxonomies with knowledge graphs, organizations can create rich semantic models that capture complex relationships and dependencies. This integration enhances the usability and flexibility of custom taxonomies, enabling advanced knowledge discovery and inference capabilities.

As data continues to proliferate, embracing AI-driven approaches to taxonomy development becomes essential for staying competitive, unlocking insights and delivering value to users. By harnessing the power of AI, organizations can transform how they organize, analyze and leverage information, driving innovation and efficiency across diverse domains.

A controlled vocabulary or full taxonomy is needed to ensure that the machine-assisted or fully automated indexing is comprehensive, regardless of what is to be indexed. Access Innovations is one of a very small number of companies able to help its clients generate ANSI/ISO/W3C-compliant taxonomies to make their information findable. Whether upgrading an existing taxonomy or creating one from scratch, we work with you on a taxonomy and thesaurus that meet your needs.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.