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From user preferences and location to time of day and weather, complex context representations have been the key to delivering personalised content. Graph databases excel at dealing with large amounts of complex data and therefore, they have been at the core of many modern real-time recommendation systems. In the near future, graph databases will play an equally important role in search personalisation.
In this talk, Michal will introduce real-world content personalization requirements and show how Neo4j has been used to implement them. He will show how much recommendation and search engines have in common and give an overview of the latest innovations in the field of search personalisation.
From user preferences and location to time of day and weather, complex context representations have been the key to delivering personalised content. Graph databases excel at dealing with large amounts of complex data and therefore, they have been at the core of many modern real-time recommendation systems. In the near future, graph databases will play an equally important role in search personalisation.
In this talk, Michal will introduce real-world content personalization requirements and show how Neo4j has been used to implement them. He will show how much recommendation and search engines have in common and give an overview of the latest innovations in the field of search personalisation.
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