semantic_searchLike it or not, the search algorithms of the future are going to be drastically different than those we interact with today. As inference and semantic technologies improve and search algorithms continue to strive to provide the best results for an individual user, it’s inevitable that they will begin to be incorporated into standard search practices.

In this post I’m going to present an overview of semantic search and why I think it is the direction search algorithms are heading.

What is Semantic Search?

Semantic search represents a major shift in the direction of search algorithms. Currently, search algorithms tracking data according to pattern detection. There are patterns surrounding keywords, backlinks, page structure, site structure, etc, each of which influences a page’s ranking. Fundamentally, the algorithm finds relevant pages because it finds pages that include the same keywords in relevant places.

Semantic search, on the other hand, refers to the ability of an algorithm to understand far more contextual aspects of a search term. It is a step on the path towards artificial intelligence and can theoretically provide better, more relevant information to users more quickly.

We are already seeing some examples of this filter into our everyday results. For example, if you search for a broad term like “current weather,” Google will infer your location (based either on current device GPS if enabled or on previous data from your searches and activity) and return the weather related to your city. This is only a first step of computational inference applied to search.

Let me use a deeper example to illustrate further. Imagine you enter a search for “famous artists with mental illness.”

Using today’s search algorithms, the results return pages and articles than include those keywords in relevant places on the page. One result is on “Creativity and Mental Illness,” and another on “50 Famous People with Mental Illness.” Each of these articles probably also includes the missing keywords somewhere in the text of the page. The search returned a result based on isolating elements of the search phrase.

A semantic search, however, would be able to understand more components implied in the phrase. It would understand that Van Gogh was a famous artist who suffered from bipolar disorder, and it would understand that bipolar disorder is a type of mental illness. Thus it might return a more relevant result on Van Gogh, even if the article didn’t include the keyword phrase.

Realistically, we are still several years away from a wide-scale adoption of semantic technology in our everyday lives. While it may take time to come to fruition, it is important as a content marketer to think about how the web will change before those changes take serious effect.

Read on to see how semantic search will change the future of SEO.