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In this article, I want to discuss a subject that may seem alien to our field of work: the Semantic Field, and demonstrate that this view is far from reality. My goal is to present this concept as one of the pillars supporting Information Retrieval in semantic systems. We will take a journey starting from Linguistic Theory and arrive at Practice in Semantic SEO.

How to remove keywords from your life.

For a long time, SEO work was reduced to a hunt for exact terms. We created content around “keywords” as if they were atomic units, devoid of any neighborhood. Even today, much of the work that countless professionals do every day is related to researching and using keywords. And to be honest, that is perfectly fine. Everyone works the way they want, believe, and can.

But I wouldn’t be myself if I claimed that this is enough. It is not. In my view, the era of Keywords should have already come to an end. I say this based on the study of algorithmic evolution, which progressed through various stages, from the launch of BERT to the arrival of models like LaMDA. Search engines like Google have moved beyond merely “reading” texts to understanding human language in a more complete way.

Learn more about the evolution of search algorithms.

Today, the essence of search is the comprehension of language. Language is the category of a system of signs, signals, or symbols—whether they are auditory, gestural, written, or iconographic—that allows for communication and the expression of thoughts, feelings, and information between individuals. Unlike “tongue,” which is a specific code of a community (such as Portuguese or French), language is a universal human faculty and a superior psychic function that enables social interaction and the construction of reality through symbolic representation.

The greatest difficulty for automated systems, including search algorithms, lies in their enormous difficulty relating to the symbolic characteristics of human language. The individual characteristics of language, therefore, reside in this arbitrary and conventional nature, where there is no necessary relationship between the sign and the object it represents, but rather an implied agreement between speakers.

In the theoretical field, language performs several functions, such as the referential (transmission of data), the emotive (expression of feelings), and the phatic (testing the communication channel).

It is in this scenario that I introduce the Semantic Field. It ceases to be a concept restricted to linguistics offices to become the foundational tool in building topical authority. And here I need to clarify my point of view on the term “topical authority.”

A topic is a fundamental thematic unit used in information organization to represent a subject, concept, or object of interest within a retrieval system, such as a search engine. We must understand a topic as an element of subject classification, and its function is to describe (or tag) the content of a document (in our case, web pages), allowing dispersed information to be grouped by semantic affinity and retrieved efficiently by users and algorithms.

Topic from the point of view of information organization.

Bringing the world of Library Science into our conversation, we understand that the individual characteristics of a topic reside in its capacity for delimitation and hierarchization. To delimit is to choose the scope; to hierarchize is to group and name.

In the theoretical field of Information Science, topics can be organized into linear structures (subject lists), hierarchical structures (taxonomies, where a “parent” topic encompasses “child” topics), or relational structures (thesauri and ontologies, which establish complex connections of equivalence and association).

In Semantic SEO work, the precise definition of a topic is the foundation that prevents ambiguity and ensures that different types of professionals working on projects, and the systems they build, interpret the term in the same way, maintaining the consistency of the content as a whole.

The topic in digital information architecture

In this scenario, the topic functions as the central node of navigation schemes and metadata. Historically, organization by topics evolved from book indexes and card catalogs used in libraries in the past to sophisticated topic modeling systems in artificial intelligence, which identify thematic patterns in large volumes of text with Big Data. Thus, a topic is not just a label, but the structural component that transforms raw data into organized and accessible knowledge.

Topical authority and topic cluster. Does that make sense?

That said, taking into account that a topic is this central element in information architecture in the digital environment, I strongly criticize the use of “topical authority” and “Topic Clusters” as the ultimate goal or strategy of a Semantic SEO project.

There is a conceptual confusion dominating the current search market. It is very important to understand that the digital marketing industry has a tendency to “rename what is already known” from time to time. The goal is to sell methodologies as if they were technological breakthroughs.

However, when we analyze this through the lens of Information Science, we realize that “Topic Clusters” and “Topical Authority” are nothing more than operational tactics, rather than the strategic compass of a Semantic SEO project. The real strategy lies in Knowledge Engineering and domain modeling, not just in the mechanical grouping of URLs.

What the market calls a Topic Cluster is, in essence, a simplified application of classification and thematic organization systems that Library Science has mastered for centuries. Organizing content by subject and establishing logical connections between its parts is a very basic function of thematic representation. Treating this as an “innovative strategy” is a mistake, as it reduces the intellectual work of meaning-making to a mere internal linking structure.

In the Semantic Workflow (SWF), the cluster is merely the structural byproduct of something much more substantial: the creation of an ontology that maps the entities and properties of a domain.

From the same perspective, “Topic Authority” is a result of consistently delivering valuable information, not a goal achieved through pre-set formulas. In Information Retrieval, authority is intrinsically linked to accuracy and recall, that is, how competent your system is in delivering the exact answer to the user’s need.

Positioning oneself as a reference in a subject is the natural consequence of an exhaustive indexing process and an information architecture that prioritizes semantic clarity, making information not only available but processable and reliable.

Therefore, we need to elevate the debate beyond these marketing nomenclatures. When we focus excessively on “clusters,” we risk creating silos of content that ignore the interconnectedness of knowledge. A topic is not an isolated element; it is part of a graph.

In my view, the strategy should be the construction of Knowledge Graphs and the use of structured data to explicitize relationships, which is far more decisive than the simple creation of a pillar page surrounded by satellite posts.

Therefore, I maintain that Semantic SEO is a discipline of Knowledge Organization. Treating these tactics as strategies is an error; we need to return them to their proper places: auxiliary tools and not the heart of the project. With this in mind, we can focus on what is decisive: contextual intelligence.

We need to create digital environments where information is relevant, meaning is preserved, and authority is irrefutable proof of intellectual significance, not just a KPI of content volume. For me, the most important aspect of organizing information is the context we create, bringing us closer to semantics.

The perspective of linguistics and the power of context.

For linguistics, semantics is the system that interacts with human thought to explain the meaning of messages. The Semantic Field, specifically, is the set of words joined by meaning. It works with the various meanings that a single word can present depending on the context in which it is placed.

What needs to be noted is that the role of context is crucial in resolving ambiguity.

Think of the term “bank”: its semantic field includes “databank,” “park bench,” “blood bank,” and “financial institution,” and each of these terms has its own particular semantic field. Each of these variations carries different cultural and intentional nuances. Without mapping this field in general and identifying each sub-semantic field, the information retrieval system can generate “noise,” delivering information to the user that is not relevant to their actual need.

It is interesting to know that our brain organizes these structures instinctively through associative series (such as Cat > Feline > Mammal). In Semantic SEO, our goal is to make these relationships explicit so that the machine can mimic this process of human understanding.

The Intersection with Library Science and Information Science

The connection between SEO and Library Science, from my point of view, is the best way to create an indispensable source of knowledge for lasting results. Information professionals have used artifacts such as Taxonomies and Thesauri for decades to organize knowledge; it makes no sense not to use all this knowledge to our advantage.

When we map a semantic field, we are, in practice, taking the first steps toward defining our Knowledge Domain (or Knowledge Model). Understanding the semantic field that “embraces” our project is a practical way to start modeling all the concepts that are part of it. After that, the path is to make the correct selection of terms that make sense for the organization owning the project.

Through the creation of explicit taxonomies, which are representations of how we organize information, we can transform unstructured text into machine-processable knowledge.

Subject indexing, a classic Library Science technique, uses the semantic field to ensure that a document is “findable” regardless of the exact term used in the search. If your website understands that “running shoe” and “running sneakers” belong to the same semantic domain, it becomes much more efficient in responding to the user.

Please understand me clearly: what I’m saying isn’t just theoretical talk; it has practical applications in semantic optimization! Let’s talk about it.

Strategic applications in semantic SEO projects

In the day-to-day of a project, the use of the semantic field translates into practical and significant actions:

1. Entity construction: mapping the semantic field facilitates the extraction of conceptual and named entities (people, places, organizations) that give substance to the content.
2. Classification and thematic organization: by exhaustively covering all the terms and properties of a semantic field, organizing and classifying them correctly, we signal to Google that the site has a high degree of trust and authority on that specific subject.
3. Semantic writing: writing with the semantic field in mind helps writers stay on topic, connecting the network of entities in that text in a way that helps search engines correctly classify the content in SERPs, reducing the chances of it being ignored due to ambiguities.
4. Alignment of concepts: Semantic SEO becomes a process of constructing meaning for the alignment of concepts, providing metadata that connects data transparently to algorithms.

Semantic-aware Workflow in practice

For this work to be conclusive, we adopt the SWF (Semantic Workflow). Our proprietary method utilizes tools from Library Science and Information Science applied to the digital environment. In summary:

• Term mapping: we identify the key concepts of a domain.
• Creating Knowledge Graphs: we consolidate the relationships between these terms through semantic markup (such as Schema.org).
• Use of semantic tools: technologies that allow the system to “learn” from searches and provide feedback to the knowledge structure.

To learn more about SWF, listen to this episode of the Semantic SEO Podcast:

Contextual intelligence as a differentiator

Understanding and applying the concept of the Semantic Field is one of the practical ways to move from traditional SEO to a new era of Web Data optimization. We live in a time when Artificial Intelligence requires information to be structured in order to be cited and understood.

Investing in information organization through semantics is not just a technical choice; it is a necessary business strategy. By providing context and eliminating ambiguities, we are not just optimizing for robots; we are building a bridge of meaning between your organization’s knowledge and the user seeking it. The future of the Web is, unquestionably, semantic.

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