When we set out to build a knowledge graph at Zalando, most people did not know how to build one, or considered machine learning as the better solution. However, endorsement from upper management led to the current project, where we use ontologies to improve the customer search and browsing experience.

There are many unique things about the way we built our ontology for Enterprise purposes. Our ontology is peer-reviewed, use case-driven, and we apply special techniques to keep the graph and our APIs and data in sync.

Communicating the graph to different professionals also has its challenges. Backend engineers and machine learning experts have a hard time understanding knowledge graph quirks. Product people accept it only if it creates a clear improvement for customers. How do you reconcile them all?

Katariina Kari
Research Engineer, Zalando Tech-Hub

Katariina Kari (née Nyberg) is a research engineer at the Zalando Tech-Hub in Helsinki. Katariina holds a Master in Science and Master in Music and is specialised in semantic web and guiding the art business to the digital age. At Zalando she is modelling the Fashion Knowledge Graph, a common vocabulary for fashion with which Zalando improves is customer experience. Katariina also consults art institutions to embrace the digital age in their business and see its opportunities.

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