What are augmentation queries
Learn what augmentation queries are and how additional search questions can enrich a topic without replacing the main intent.
SEO Glossary
Here you will find the SuperSEO glossary with clear explanations of semantic SEO, query analysis, entities, structure, and related concepts.
Learn what augmentation queries are and how additional search questions can enrich a topic without replacing the main intent.
Learn what boilerplate links are, how search engines may weigh fixed navigation and footer links, and when they provide less context than editorial links.
Learn what context words are and how surrounding words help you more precisely interpret terms, entities and search intent.
Learn what contextual vectors are and how vector representations with context help determine meaning and relationship between words or passages.
Learn what correlative queries are and how queries with related patterns help with intent, topic, and SERP analysis.
Learn how semantic rules for titles help to clarify subject, intention and distinctive meaning in the page title.
Domain list terms are terms that are characteristic of a particular knowledge domain and help determine where content belongs in content terms.
Entity connections are substantive relationships between entities, such as concepts, brands, persons, places or objects.
Entity definitions are definitions that clarify what an entity is, to which class it belongs and what distinguishes it.
Learn what intent templates are and how fixed intent patterns help cluster, write and review SEO content.
Learn what internal links are, why they strengthen SEO and how to use them logically for structure and navigation.
Learn how query semantics helps you understand the intent behind a search query, even when words are ambiguous, incomplete, or carelessly chosen.
Learn what question and answer elements are and how question, answer, context and evidence parts together form a useful SEO explanation.
Learn what rare entity attributes are and why rare entity attributes can be important for specific queries and semantic coverage.
Term vectors are numerical representations of terms that allow systems to calculate relationship, distance, or importance.
Types of attributes in semantic SEO are types of properties that allow you to describe entities more specifically.
Types of content main supplementary and ads distinguishes main content, supporting content and advertising content on a page.
Learn what ambience optimization means: improving the meaning environment around a topic so context, entities, and internal relationships reinforce each other.
An answer seeking query is a search query where someone primarily expects a short, direct answer.
Learn what boilerplate content is and how repeated text blocks in templates can affect SEO signals, quality, and page differentiation.
A canonical query is the preferred wording that represents a group of similar search queries.
Learn what a categorical query is and how searches for types, categories, or classes differ from specific entity queries.
A central entity is the most important entity that a page, query, or text passage revolves around.
Learn what central search intent is and how to distinguish the dominant need behind a search query from secondary intents.
Learn what a co-occurrence matrix is and how terms appearing together support semantic analysis, topical relationships, and content coverage.
Learn what a complex adaptive system is and why search engines and search ecosystems do not respond linearly to individual SEO adjustments.
Learn what content configuration means and how order, blocks, templates and page parts together drive the meaning of content.
Learn what contextual domain means and how the area of knowledge surrounding a term determines which meaning, examples and internal links make sense.
Learn what a contextual layer is and how additional context layers help you interpret words, passages and entities more clearly.
A discordant query is a query that deviates from the expected cluster, dominant intent, or normal meaning relationship.
Learn what discourse integration means and how coherence between sentences, passages and questions helps you better understand content.
EAV in semantic SEO uses entity, attribute and value to describe entities in a concrete and structured manner.
The EAV model describes information as entity, attribute and value: an entity, a property and the value of that property.
An entity seeking query is a search in which someone searches for a specific entity, such as a brand, person, place, product or well-known concept.
Entity SEO focuses on entities, properties and relationships, while traditional SEO relies more heavily on individual keywords and page optimization.
A factual query is a search in which someone is looking for a verifiable factual answer.
Learn what historical data means in SEO and how historical performance, crawls, rankings and content changes help to better explain trends.
Index partitioning is the process of dividing index data into logical parts so that documents can be stored, found, or reviewed more efficiently.
A knowledge domain is a defined knowledge area with its own concepts, entities, relationships and rules.
Learn the difference between macro context and micro context in semantic SEO, with examples for query interpretation and content review.
Mid page query refinement is refining a search query while someone is already working on a page or within a search experience.
Learn what minor intent means and how secondary search needs can enhance a page without crowding out the main intent.
Learn what modality means in language and SEO: how possibility, necessity, certainty and desirability change the meaning of a sentence.
Multi stage query processing means that a search query is processed in multiple steps before results are selected.
A natural language query is a search in ordinary human language, often as a complete question or colloquial sentence.
The non-variable portion in query is the fixed part of a query template that remains the same while other parts change.
A non-factual query does not ask for one verifiable fact, but for interpretation, advice, preference or assessment.
Learn what onomastics means and why onomastics can be relevant for entities, brands, people and place names in semantic SEO.
An ontology is a formal organization of entities, properties, classes and relationships within a knowledge domain.
Open information extraction is the automatic extraction of facts and relationships from free text without a completely fixed scheme in advance.
Page segmentation is the division of one page into meaningful parts such as main content, navigation, footer, advertisements and FAQ.
Quality threshold is the minimum quality limit that content must meet before publication or indexation is sensible.
Query ambiguity means that a query has multiple possible meanings or intentions.
Learn what query analysis means and how analyzing words, intent, context and ambiguity helps you better answer search queries.
Query breadth describes how broad or narrow a query is and how many possible intents or subtopics remain open.
Query expansion is expanding a search query with additional terms, synonyms or related concepts to enable better matching.
A query network is a network of searches that are connected via intent, topic, SERP overlap or search behavior.
Query parsing is the process of parsing a query into components that a system can interpret.
A query path is the order in which someone uses multiple queries to arrive at an answer or decision.
Query processing is the processing of a search query so that a system can find appropriate documents or answers.
Learn what query rewrite is and how search engines or SEO systems can rewrite queries to better match intent and relevant results.
Query SERP mapping is the act of linking a query to the type of search results that the SERP actually shows.
A query template is a reusable pattern that allows multiple queries to share the same structure.
A query term is an individual word or meaningful part within a search query.
Query type is the category to which a search query belongs based on intent, form, or expected outcome.
Query word lemmatization brengt verbogen querywoorden terug naar hun woordenboekvorm.
Query word voting reduces words in a query to a stem form, often coarser than lemmatization.
Learn what ranking signal consolidation means and how clear canonical choices, internal links and content delineation bundle SEO signals.
Learn what ranking signal dilution is and how fragmented URLs, duplicates and weak internal links can weaken SEO signals.
A representative query is a search that well represents a broader intent, cluster or topic.
A represented query is a query that is represented by another query, page or cluster.
Learn what search engine communication means: how content makes it clear what a page is about through structure, language, internal links and entities.
A seed query is a starting query with which you start further keyword, topic or SERP research.
Semantic distance describes how far two words, concepts or documents are from each other in content terms.
Semantic relevance is substantive relevance based on meaning, intention and context, not just an exact word match.
Semantic role labeling determines what role words or phrases play around an action, such as performer, object, time or place.
Learn what semantic SEO means and how to build stronger SEO pages with entities, context, and search intent.
Semantic SEO and its future is about the evolution of SEO towards meaning, entities, intent and AI-enabled search experiences.
Semantic similarity describes how closely two words, passages or concepts are substantively similar.
A semantic triple captures meaning in three parts: subject, predicate and object.
The Semantic Web is the idea that web information becomes machine-readable by making meaning and relationships explicit.
A sequential query is a query that is part of a series of consecutive queries.
Learn what source context means and why origin, environment and reliability of information matter in semantic interpretation.
Learn what subject-object-predicate means and how this structure helps to more clearly describe facts, entities and relationships in semantic SEO.
Learn what a substitute query is and when a substitute query formulation can better represent the same intent than the original query.
Learn what supplemental index means, why weaker or less central pages can be treated separately and what this means for SEO analysis.
A synthetic query is an artificially created search query for analysis, testing or expansion.
A taxonomy is a hierarchical arrangement of concepts, categories or entities.
Learn how Google Search evolved from keyword matching to semantic interpretation, entities, intent, and AI-powered search experiences.
Learn what topical authority means and how to build authority through complete, coherent content around a topic.
Learn what topical entry means and how a topic can function as an entry point in a knowledge structure or topical map.
Learn what uncertain inference means and how search and SEO systems still choose likely interpretations under uncertainty.
Learn what update score means in SEO and how change, topicality and content refreshment can be taken into account without every update automatically being better.
The variable portion in query is the part of a query template that changes while the intent structure remains the same.
Learn what website segmentation is and how dividing a site into logical sections helps with crawlability, analytics and topical authority.
Learn what word adjacency means and why words placed next to each other sometimes provide a stronger meaning signal than individual terms.
Learn what word proximity is and how distance between words helps to better assess meaning, phrase relevance and query matching.
A word vector is a numerical representation of a word that allows a system to calculate meaning relationships.
Write meta description semantic means writing a meta description that clearly summarizes meaning and intent instead of just using keywords...