The application's tech stack is introduced alongside key vocabulary from the tourism industry to set the context for the project.
A walkthrough of the "Make My Day" web application shows how a user answers a quiz to generate a personalized, actionable daily plan for Vienna.
The C4 model is used to explain the high-level architecture, showing how the application interacts with the central data hub and various external services.
An exploration of specific APIs, including an opinionated location aggregation service and an oEmbed-based service for embedding UI components like maps.
The core logic for creating itineraries is a 10-step procedural algorithm that incrementally fills a pre-defined day structure with matching points of interest.
Logistic regression is used to classify places of interest based on atmosphere and weather suitability, highlighting the challenges of human bias in data labeling.
An ETL-like pipeline retrieves structured and unstructured data, uses NLP to link it to points of interest, and aggregates it into a knowledge graph using schema.org.
The project's key takeaways, including the limitations of NLP in Node.js, led to evolving the prototype into a reusable framework for other tourism destinations.
Jobs that call for the skills explored in this talk.