Spotify Ab

Maryam Aziz

Benjamin Austin Carterette

Jesse Anderton

David Bourgin

Alice Yiqing Wang

Hugues Bouchard

Enrico Palumbo

Gustavo Penha

An adaptive multi-model item selection method, comprising: receiving, from one of a plurality of client devices, a request including a client-side feature vector representing a state of the client device; determining, by an advocate model, a probability distribution of a plurality of specialist cluster models from the client-side feature vector; choosing, by a use case selector, a cluster corresponding to a use case from the probability distribution; and obtaining, by the use case selector based on the cluster (i.e., the cluster that was sampled by the user case selector), a specialist cluster model from the plurality of specialist cluster models.

Adaptive multi-model item selection systems and methods

An electronic device provides, to a model trained to generate synthetic queries, information corresponding to a first media content item and a first value for a parameter indicative of query specificity. The device receives, from the model trained to generate synthetic queries, a first query corresponding to the first media content item, wherein the first query is generated in accordance with the first value for the parameter indicative of query specificity. The device provides, to a client device for display at the client device, the first query and receives user selection of the first query. In response to the user selection of the first query, the device provides a first result set of media content items for the first query.

Systems and methods for generating synthetic queries

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Princeton Junction, NJ, United States of America

Maryam Aziz