Intro
Semantic SEO focuses on search intent, context, and relationships between words, entities, and topics rather than just keywords. Understanding key Semantic SEO terms is crucial for optimizing content and improving search visibility. Below is a glossary of essential terms and their meanings.
1. Semantic Search
Semantic search refers to search engines' ability to understand intent and context rather than just matching keywords. It uses natural language processing (NLP) to improve results.
2. Entity
An entity is a recognizable object, concept, or person in Google's Knowledge Graph (e.g., "Elon Musk," "Ranktracker," "New York City"). Entities help search engines understand topics better.
3. Knowledge Graph
Google’s Knowledge Graph is a database that connects entities and their relationships. It powers Google’s Knowledge Panels and featured snippets.
4. Latent Semantic Indexing (LSI)
LSI is a technique that helps search engines find related terms and concepts associated with a topic, improving contextual relevance.
5. E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness)
A key ranking factor used by Google to evaluate content credibility. Websites with strong E-E-A-T signals rank higher in search results.
6. NLP (Natural Language Processing)
A field of AI that enables machines to understand and process human language. Google’s BERT and MUM algorithms use NLP to improve search results.
7. BERT (Bidirectional Encoder Representations from Transformers)
A machine learning algorithm introduced by Google to better understand search queries in context.
8. MUM (Multitask Unified Model)
An advanced AI model used by Google to analyze multiple content formats (text, images, video) and multiple languages for deeper understanding.
9. Structured Data (Schema Markup)
A form of organized data that helps search engines understand page content. Common schema types include:
- Article Schema
- FAQ Schema
- Product Schema
10. Topic Clusters
A content strategy that groups related articles around a pillar page. Helps boost authority and improve internal linking.
11. EAV Model (Entity-Attribute-Value)
A data model that structures entities, their characteristics, and their values, helping Google better understand content relationships.
12. Subject-Object-Predicate (SOP)
A structure that defines relationships between entities in semantic SEO. Example:
- Subject: Google
- Predicate: ranks
- Object: high-quality content
13. Taxonomy
A hierarchical system used to classify and structure content on a website, improving site organization and search visibility.
14. Page Segmentation
The process of dividing a webpage into main content, supplementary content, and ads, helping search engines prioritize information.
15. Central Entity
A core subject that connects multiple topics and content pieces, improving SEO relevance and rankings.
16. Semantic Keywords
Words and phrases related to the main keyword, improving content depth and search engine understanding.
17. Query Intent (Search Intent)
The reason behind a user’s search. The four main types are:
- Informational – Looking for knowledge
- Navigational – Searching for a specific website
- Transactional – Ready to make a purchase
- Commercial Investigation – Comparing options before buying
18. SERP Features
Enhanced search result elements like featured snippets, knowledge panels, and people also ask boxes.
19. Canonicalization
A method to prevent duplicate content issues by specifying a preferred version of a page using the rel="canonical" tag.
20. Google RankBrain
An AI algorithm that helps Google adjust rankings based on search behavior and relevance.
Conclusion: Mastering Semantic SEO Terminology
Understanding Semantic SEO terms is essential for optimizing content, improving rankings, and staying ahead in search engine algorithms.
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