Empire Technology Development LLC

Lemon Inc.

Beijing Volcano Engine Technology Co., Ltd.

Han Qian

Kai Xie

Junwei Cao

Junwei Li

The present disclosure provides a data storage method, an apparatus, an electronic device and a storage medium. The data storage method includes: acquiring at least one piece of feature data to be stored in a target storage system, wherein each piece of the feature data has a corresponding primary key respectively; for each piece of the feature data, determining, from a plurality of first time partitions corresponding to the target storage system, a target time partition to which a data occurrence time of the feature data belongs; and allocating, based on a total number of buckets corresponding to the target time partition and a primary key corresponding to the feature data, a corresponding bucket to the feature data, and storing the feature data in a storage space that is associated with the corresponding bucket of the feature data.

Data storage method and apparatus, electronic device, and storage medium

A data processing method, apparatus, device, and storage medium are provided. The method includes acquiring a data reading task; determining the target feature data from a data file stored in a target storage system based on the data reading task and metadata corresponding to the target storage system; reading the target feature data from the data file based on operation semantic information corresponding to the target feature data, and determining the read target feature data as the first target feature data; and merging the first target feature data to acquire target merged feature data in the case that the size of data volume of the read first target feature data meets a preset condition, and repeating the process of reading and merging the first target feature data until a completion of reading of the target feature data in the data file.

Data processing method, apparatus, electronic device, and storage medium

An example method to determine a quality-of-experience (QoE) metric for a network communication includes receiving a media signal from the network communication, wherein the media signal includes a voice component, extracting an experience indicator from the voice component, wherein the experience indicator is a voice feature descriptive of a service quality of the network communication, evaluating the experience indicator, retrieving a quality-of-service (QoS) metric if the evaluated experience indicator reflects the service quality of the network possibly being subpar, and determining the QoE metric for the network communication based on the evaluated experience indicator and the retrieved QoS metric for the network communication.

Quality-of-experience measurement for voice services

Technologies are generally described for determining a quality-of-experience (QoE) of a network communication. In some examples, a process for determining a QoE metric for a network communication includes receiving a media signal from the network communication. The process may also include extracting an experience indicator from the media signal, wherein the experience indicator corresponds to a participant's subjective usage experience associated with a service quality of the network communication, and determining the QoE metric for the network communication based on the experience indicator and a quality-of-service (QoS) metric for the network communication.

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Beijing, China

Han Qian