In the world of search, we used to focus on “exact matches.” In the world of AI and modern ontologies, the real value lies in inexact matching.
Think about food science or product recommendations. If a customer wants “Buffalo Wings” but they aren’t available, what is the viable alternative? Is it fried shrimp? It depends on the context—is it the texture they want, or the spicy dipping sauce?
A simple keyword search fails here. A raw LLM might guess. A robust ontology understands the attributes that make a “match” successful. This level of nuance is what separates a frustrating chatbot from a truly intelligent assistant.