Semantic Search Patterns

🧠 You can't build a semantic content network without understanding the semantic search patterns of your target users.

🔍 There are patterns in how users search for information.
🔗 And there are relations in the words they use to search for that information.

✨ Based on the predicates (verbs) used in the queries, the themes will be different.

📌 Example Query:

"How to improve X"

The nouns replacing "X" should have a thematic similarity due to the predicate "improve."

🟢 Google auto-completes the following nouns for "X":

• 🌴 English
• 🌴 English Writing Skills
• 🌴 Vocabulary
• 🌴 Listening Skills
• 🌴 Communication Skills

📌 Any change in the predicate will result in a change to the overall theme.
🔄 Google auto-complete would also vary based on different predicates.

❓ But why are predicates so important?

A semantic search engine organizes its index and processes queries based on the EAV (Entity, Attribute, Value) database structure.

📚 This EAV model relies on predicates to distinguish contexts and subtopics.

That’s why understanding the verbs in a query is so crucial.
🧩 These verbs help build a semantic content network by signaling the thematic words.

☕ Take the example of the noun "coffee":

When paired with different verbs (predicates), the thematic direction changes:

✅ "Brewing coffee" signals:

• 🔸 Grinder
• 🔸 Filter
• 🔸 Kettle
• 🔸 Beans
• 🔸 Barista

✅ "Growing coffee" signals:

• 🔸 Plantation
• 🔸 Farmer
• 🔸 Harvest
• 🔸 Beans
• 🔸 Soil

🔍 All such thematic words appear based on the verb affecting the noun (in this case, "coffee").

🧠 Why this matters:

Understanding search patterns helps you plan your semantic content network more effectively.
It lets you factor in user behavior and intent, giving your content a strategic SEO edge.