A decade ago, optimizing for search engines meant grabbing as many back-links as possible and including more keywords than the content needed. Back then, search engine optimization meant understanding how search engines generated results so that we could reverse-engineer content that ranks higher.

Search engine understanding has evolved, has have how we optimize for it. Identifying keywords is no longer enough. It is now all about understanding what the words mean. Semantic search describes a search engine’s attempt to generate the most accurate results possible by understanding the searcher’s intent, the context of the query, and the relationships between the words.

One of the first developments around semantic search was done by Google and known as the Knowledge Graph -developing the importance of entities and context over strings of keywords. The Knowledge Graph collected information considered public domain and the properties of each entity.

As user patterns change and technology morphed, new players like smart assistants and mobile assistants came on the scene. Now, more consumers are bypassing the keyboards on their computers and phones when searching for information.

The capabilities of artificial intelligence are also expanding, and voice search has the potential to change the landscape completely. It’s a development that presents new challenges in search engine optimization.

Going beyond the static dictionary meaning of a word or phrase to understand the intent of a searcher’s query within a specific context, creates opportunities to learn from past results. Creating links between entities, a search engine might then be able to deduce the answer to a searcher’s query, rather than provide multiple links that may or may not provide the correct answer.

Semantic search has emerged from the semantic web. The semantic web is built on ontologies. In the field of information science and computers, an ontology is basically a framework for facts and information that constitute a system of knowledge. Ontologies allow for the analysis of specific inputs or sets of inputs based on a network of related factors.

Search is all about findability. Semantic search is about perfecting that.

Melody K. Smith

Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.