What is Semantic Search?
A mathematical method used to determine the relationship between terms and concepts in content. The contents of a web page are crawled by a search engine and the most common words and phrases are collated and identified as the keywords for the page.
Semantic Search can be broken down into three components.
Latent Dirichlet Allocation (LDA) – is a generative statistical model that allows sets of observations to be explained by unobserved groups that explain why some parts of the data are similar.
Latent Semantic Indexing (LSI) – is a mathematical method used to determine the relationship between terms and concepts within the content.
Term Frequency and Frequency-Inverse Document Frequency (TF-IDF) – This uses term frequency weighting schemes and their predetermined weighted relationships to determine quality.
Why Did This Come About?
This partially came a result of keyword stuffing and spamming. Along with a need to better parse and understand contextual cues from search behavior.
How Does this Apply to SEO?
LSI keywords (Latent Semantic Indexing) are keywords that are semantically related to your primary keyword. This does not necessarily mean including synonyms of target keywords.
The image of The Simpsons shows a simplified example of semantic search. The diagram shows how entity-based search seeks to connect various entities. This is how Google creates more depth in response to searches.