📌 Understanding the Dependency Tree & POS Tags in NLP

According to the Dependency Tree, words are tagged by Natural Language Processing (NLP) technologies based on their context and type. However, understanding a word’s context is not always easy.

🔍 How Do Search Engines Understand Context?

A Search Engine can use phrase-based occurrence correlations, such as Word2Vec, to understand a word’s context.

• For instance, according to Hidden Markov Models (HMMs):
  • 📌 40% chance of being a noun 🏷️
  • 📌 20% chance of being an adjective 📝
  • 📌 20% chance of being a number 🔢
• Example: If the word "can" follows "the", the model understands that "can" is used as an object 🏆 rather than a modal verb ⚡.

🏷️ Common POS Tags in NLP

• CC: Coordinating Conjunction (e.g., and, but, or) 🔗
• CD: Cardinal Digit (e.g., one, two, three) 🔢
• DT: Determiner (e.g., the, this, those) 📍
• EX: Existential "there" (e.g., there is, there exists) 🌍
• FW: Foreign Word 🗣️
• IN: Preposition/Subordinating Conjunction (e.g., in, on, before) 📌
• JJ: Adjective (e.g., big, small, happy) ✨
• JJR: Comparative Adjective (e.g., bigger, faster, smarter) 🚀
• JJS: Superlative Adjective (e.g., best, biggest, strongest) 🏆

🔥 Why Are POS Tags Important in SEO?

Content format and POS Tags are interconnected. If a user query has a comparison intent, certain POS Tags will be prioritized by the Search Engine.

• ✅ Example: If a query contains words like:
  • 🔹 "best", "biggest", "fastest" → Comparative Adjectives (JJR, JJS)
  • 🔹 "best 5" → The Search Engine expects a listicle format 📋
• 🔍 SEO Strategy:
  • ✔️ Relevant POS Tags 🎯
  • ✔️ Well-structured lists 📜
  • ✔️ Proper sentence structures 🏗️

💡 Pro Tip: I always educate my authors to think like a Search Engine 🤖. This helps them create structured, clear, and informative content that aligns with search algorithms and enhances readability.

🔹 "You shall know a word by the company it keeps." – Choose your words wisely! 🎯