Part of: SEO Best Practices
Part of: Search Engine Algorithms
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Updated:
by Wayne Smith
The entity relationships model is part of natural language processing and is used to use to build knowledge graphs; understand query intent; And, can be applied to semantic search.
- The evolution from Search Keywords to Search Entities
Instead of just storing a keyword and its related page as an index; an entity stores related entities, properties, and other details concerning the query term. By checking content for the related entities the content can be quantified as to how well it covers the query.
- Search Query and Insights into Entities
User intent, or what Natural Language Processing determines is the search intent, shares the entity data and provides an insight into how relevancy is determined.
- Evolution of Branded Websites to Search Entities
Search engines have evolved over time both brands and domain names are treated like a entity. With understanding a local business has properties such as an address and hours of operation.
Semantic Content
Semantic content is using words closely related to the topic of a webpage on the webpage. Generally speaking, these related words are entities.
- LSI (latent semantic indexing) and content relevancy
Using keywords only to determine relevancy comes down to keyword density, which does not always produce quality search results. Better results can be made by qualifying the results as relevant by checking for words related to the keyword. Google does not specifically use latent semantic indexing, but does use entities, which is more of a hyprid solution.