Ontology Graph Database & AI Identifying Complex Patterns in Any Dataset
AI Summary
In this video, Christopher Royse presents an innovative project combining ontologies, a large marketing dataset, and AI automation to identify complex behavior patterns among customers and marketers. Key highlights include:
- Overview of building a marketing behavior prediction ontology to forecast both customer and marketer behaviors (0:43).
- Utilization of a real-world dataset from a major Brazilian company to test the ontology (2:01).
- The concept of a “Gap Analyzer” to refine the ontology to fit the dataset perfectly (2:57).
- Mapping data into a GraphDB graph database using Excel (4:00).
- Executing SPARQL queries to uncover intricate relationships and triggers, such as drivers of purchase behavior (4:38, 6:05).
- Creation of a detailed testing plan leveraging Gemini AI for a structured and automated coding and testing phase (8:40, 10:48).
- Discussions on applying this methodology not only in marketing but across various fields like finance and healthcare, urging viewers to unlock the hidden potential in their data (7:30-8:05).
The video emphasizes the potential ROI from untapped datasets and encourages viewers to explore what complex patterns they might uncover within their own datasets. For more related content, viewers are encouraged to like and subscribe to the channel.
Github AI Coding Setup: GitHub Repository
LinkedIn: Christopher Royse