Tencent Technology (shenzhen) Company Limited

Zte Corporation

Tencent Technology Company Limited

Pei Duan

Jun Liu

Bo Zheng

Zhibin Liu

Mengbi Lei

Shan Wang

Zhaobi Wei

A method for updating a recommendation model based on artificial intelligence includes: acquiring sample user data and sample recommendation object data, the sample recommendation object data including data related to sample media objects; generating model updating sample characteristics according to the sample user data and the sample recommendation object data, the model updating sample characteristics including sub-characteristics of at least two characteristic dimensions; inputting the model updating sample characteristics into the recommendation model to update the recommendation model, the recommendation model updated performing recommendation on media objects, and performing local sparsification on model parameters meeting a model sparsification condition in response to determining that the corresponding model parameters of the sub-characteristics in the model updating sample characteristics meet the model sparsification condition in the process of updating the recommendation model.

Method and apparatus for updating recommendation model, computer device and storage medium

Provided is a phase-locked loop circuit, a method for configuring the same, and a communication device. The phase-locked loop circuit includes a phase-locked loop main circuit and a phase temperature compensation circuit. The phase temperature compensation circuit includes at least one phase delay unit connected to the phase-locked loop main circuit and configured to generate a phase shift as a result of a temperature change for cancelling out a phase shift generated by the phase-locked loop main circuit as a result of a temperature change.

Phase-locked loop circuit, configuration method therefor, and communication apparatus

Aspects of the disclosure provide a method of determining types of user geographical locations. A target geographical location corresponding to a plurality of uploading times can be obtained. At least one time-location type mapping relationship table can be obtained. Based on the obtained at least one time-location type mapping relationship table, for each of location types in the at least one time-relation type mapping relationship table, a sum of probability values of the respective location type can be calculated to obtain a degree that the target geographical location belongs to each of the location types. Each of the probability values corresponds to one of the uploading times of the target geographical location. Which of the location types corresponds to the target geographical location can be determined according to the degrees that the target geographical location belongs to each of the location types.

Method and apparatus for identifying types of user geographical locations

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Shenzhen, China

Pei Duan