Semantic search is search that understands the meaning of a natural language query as opposed to viewing search terms as keywords. For example, a common natural language search would look like this: “how did Tokyo become a megacity?” A semantic search would interpret this beyond simplistic analysis of keywords such as “Tokyo” and “megacity.” It would understand that the user is looking for information about the history of Tokyo and how its population became so large. Simplicable brought this interesting information to us in their article, “What is Semantic Search?”
To properly use semantic search, a search engine back end is required that can discover, rank and index knowledge resources. In addition, it requires natural language processing capabilities. Natural language processing is typically based on artificial intelligence as machine learning is required to tackle the complexity of natural languages such as English. You know, understanding the nuances of bittersweet and civil war.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.