Associative Knowledge Graph of the American Car Market



The case involves developing and validating a recommendation system and car price predictor using a Knowledge Graph, which replaces generic ML models and data structures, to represent the American used car market.


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Exploring the power of Multi-Associative Graph structures in automotive R&D


Our client is the research branch of a large automotive corporation. They are solely responsible for R&D activities for the automotive manufacturer.

Together with their researchers, we have decided to validate and test the concept of using a Multi-Associative Graph Structure, or simply a Knowledge Graph, as a replacement for generic ML models and data structures to represent the American car market – focusing on the used cars currently being offered and their associations with publicly available datasets regarding vehicles in general.

We have developed a recommendation system and car price predictor based on the graph.

For that project, the used car data from cars.com (over a million vehicles of different brands) was gathered to build a knowledge graph. The data was also associated with other available datasets, including information regarding CO2 emissions or charger availability and locations in the US.

Finally, we have validated the performance of knowledge graphs compared to regular ML tools and algorithms: regression, clustering, and pattern mining.



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The controller of the data within the scope provided above is Grape Up Spółka z ograniczoną odpowiedzialnością with its seat in Żółkiewskiego 17A, 31-539 Kraków, Poland, KRS no. 0000513816. The data will be processed in order to contact you and in case you give us your consent - to provide information about our products and services. You have the right to access the data, to receive copies, to rectify, delete or demand to limit their processing, to object to processing and to withdraw your consent for marketing contact – by sending us an e-mail: info@grapeup.com. For full information about processing of personal data please visit Privacy Policy.