“Semantic search” is the concept of a search engine applying intent and context to the results it
provides the searcher.
Semantic search seeks to improve search accuracy by understanding the searcher’s intent and the contextual meaning of terms as they appear in the searchable dataspace.
With the release of the Hummingbird algorithm in 2013, Google became more able to analyze full
questions (as opposed to analyzing searches on a word-by-word basis).
The search engine also understood that any single word could have multiple meanings, and it used context to discern which meaning might be accurate, often using a searcher’s own history to provide context.
That’s one reason why you and I might get different results for the same search, or you might get two different results if you use two different browsers for the same search. It also takes in account what other people click on in search results using the same term.
Here’s a screenshot of the results I get on Chrome for the search term “apple”:
Because the Apple brand is often searched for, and I do a lot of tech-related searches, this result
makes sense for me. I’ve also been to the Portland Nursery site numerous times over the last year, so
that result makes sense as well.
If I’d given Google a bit of semantic help by including another word or two (such as “phone,” “watch,” “tree,” Granny Smith”, etc.) the results would have been very different:
Semantic search helps engines offer searchers content from multiple authoritative sources that align
with their expectations and perceived needs.