Patent ID: 11870937
Assignee: CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD.
Field: Telecommunications (Electrical engineering)
Classification: CPC H  G  Y | IPC G  H

Claim 6:
7. An Internet of Things (IoT) system for smart gas call center feedback management, comprising a smart gas user platform, a smart gas service platform, a smart gas management platform, a smart gas sensor network platform, and a smart gas object platform, and the smart gas management platform being configured to:
receive a call message of a target customer through a call center, and a content of the call message being related to a gas business;
convert the call message to a text message;
determine a service category corresponding to the text message; and
determine, based on the service category, the feedback mode; wherein the determining, based on the service category, the feedback mode comprises:
determining, based on one or more of a service category of a message of other customers, a feedback mode of the other customers, and a service category of a message of the target customer, the feedback mode of the target customer through a preset algorithm; wherein the preset algorithm comprises:
establishing a training data set, a sample of the training data set including the service category of the message of the other customers and the feedback mode of the other customers; finding N counts of messages of the customers with the shortest distance to the message of the target customer in the training data set, and if among the N counts of messages, the messages in a feedback mode A are the most, then the feedback mode of the target customer is A; wherein the distance is related to a service category similarity, a real-time pipeline network situation, a customer positioning similarity, and an emergency similarity of the call message, the emergency similarity being predicted using a prediction model, the prediction model being a machine learning model including a first embedding layer, a second embedding layer, and an emergency similarity prediction layer; wherein
an input of the first embedding layer includes a text message of the target customer and a service category of the target customer, and an output includes a target customer feature;
an input of the second embedding layer includes a text message of the other customers and a service category of the other customers, and an output includes other customer features; and
an input of the emergency similarity prediction layer includes the target customer feature, the other customer features, a real-time pipeline network situation, a customer positioning of the target customer, and customer positionings of the other customers, and an output includes an emergency similarity

in response to the feedback mode being manual feedback, determine a target operator through the call center to feedback a call of the target customer; and
in response to the feedback mode being automatic feedback, determine a feedback content through the call center and send the feedback content to the target customer.