Tourism Media Automates Travel Content Generation with Neo4j Aura at a Massive Scale

The Challenge

Tourism Media produces dynamic travel content for hundreds of thousands of destinations across the world.

Travel content is highly reusable for similar places, but each piece has to be customized and refreshed regularly for both geographical and seasonal reasons. And when it comes to data, geography is highly unstructured and difficult to model.

The Tourism Media team tried to fit their geographical data into a relational data model, but its predefined, columns-and-rows structure made it difficult to navigate that data and produce relevant, meaningful content in a scalable way.

"If we're generating content around a ragged hierarchy like geography, how do we do that in a way that makes sense and scales?" said Terry Franklin, a freelance consultant specializing in Neo4j who worked with Tourism Media on its implementation. "For example, if we produce photos for the country Singapore, how do we make sure that they also appear on pages that understand Singapore to be a city?"

Tourism Media wanted a way to ask complex questions of data that is highly connected and hierarchical without lots of JOINs and long-running queries. They wanted agility for handling challenges such as handling route mapping for cruises around the world, translating local content into multiple languages, and automatically serving up top rated local hotels – in short meeting needs of travelers today and tomorrow.

The Solution

With the help of the Neo4j support team, Tourism Media migrated their data to the cloud, and it was quickly ready for production.

The Tourism Media graph is flexible and expanding, with new data sources added to enable new products. Standard content templates use aggregated data coupled with simple, repeatable queries to create content for hundreds of thousands of destinations. Relationships map geographical hierarchies and allow context to be added on top of each template. Ontology-based weighting is applied to tags to provide relevant recommendations for similar places.

Using only GraphQL, Tourism Media can now ask complicated questions of their knowledge graph.

"Neo4j, GRANDstack, and APOC really fit well together, because they allowed us to import all the data into the graph in a way that truly represents geography and ask the questions in GraphQL in the exact same shape that we expect the answer back," Franklin said.

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