The process of using automated tools (such as crawlers, scrapers, or AI systems) to analyze large volumes of digital content—usually text, images, or structured data—to extract patterns, insights, or to train machine learning models.
In Practical Terms, TDM Involves
- Text Mining: Extracting information from unstructured text (e.g., articles, books, social media posts).
- Data Mining: Analyzing structured or semi-structured datasets (e.g., tables, metadata, logs).
- AI Training: Feeding vast amounts of digital content into machine learning algorithms to help models learn patterns, language, or visual features.
Common Uses of TDM
- Training generative AI models like ChatGPT, Claude, Midjourney, or Bard
- Sentiment analysis in marketing or finance
- Academic research and bibliometric analysis
- Competitive intelligence or trend monitoring
TDM is at the center of debates about AI ethics and copyright because many AI systems are trained using massive datasets scraped from the open web, often without the consent of the original creators. The TDM Reservation Protocol is one way for creators to signal that their content is not available for this kind of use, especially under EU copyright law.
Related Martech Zone Content
