Website Content Analysis: Keyword and Terminology Extraction. Implementation on Apify

2026-02-21 · Source: NLP on Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Software Development & Engineering · Depth: Intermediate, short

Summary

The article details a process for terminology and keyword extraction from website content, which involves automatically collecting vocabulary and relevant terms to summarize content, identify main topics, and pinpoint specific language. This method is useful for competitive analysis, SEO keyword research, and trend identification. The process outlines steps including language recognition, text preparation (removing punctuation, accents, lowercasing), generating and counting n-grams, cleaning the n-gram list by removing stop-words and applying frequency/length rules, separating uni-grams from n-grams (n≥2), and sorting to identify Top-K keywords. The entire workflow is implemented as an actor on Apify, a platform for web scraping and data extraction, allowing users to configure a starting URL and seed keywords to generate keyword lists and Word Clouds in JSON, CSV, or SVG formats.

Key takeaway

For SEO specialists or content strategists analyzing competitor websites, understanding this keyword extraction methodology is crucial. You should consider using tools like Apify's actor to automate the process, providing insights into content summaries, main topics, and specific terminology. This can directly inform your keyword strategy and content development, helping you identify new trends and optimize your own website's visibility.

Key insights

Automated keyword and terminology extraction from websites aids content analysis, SEO, and trend identification.

Principles

• N-grams capture multi-word concepts.
• Stop-word removal enhances keyword relevance.
• Frequency sorting identifies key terms.

Method

The method involves language recognition, text cleaning, n-gram generation, stop-word removal, separate uni-gram and n-gram lists, frequency-based sorting, and optional seed keyword expansion for website content analysis.

In practice

• Use NLTK or spaCy for NLP tasks.
• Employ BeautifulSoup for HTML parsing.
• Run the Apify actor for website analysis.

Topics

• Keyword Extraction
• N-gram Analysis
• Natural Language Processing
• Web Scraping
• Apify Platform

Code references

• pemistahl/lingua-rs

Best for: Data Scientist, Software Engineer, Marketing Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by NLP on Medium.