Systems, methods, and media for causing an action to be performed on a user device are provided. In some implementations, the systems comprise: a first user device comprising at least one hardware processor that is configured to: detect a second user device in proximity to the first user device; receive a user input indicative of an action to be performed; determine a plurality of candidate devices that are capable of performing the action, wherein the plurality of candidate devices includes the second user device; determine a plurality of device types corresponding to the plurality of candidate devices; determine a plurality of priorities associated with the plurality of candidate devices based at least in part on the plurality of device types; select a target device from the plurality of candidate devices based at least in part on the plurality of priorities; and cause the action to be performed by the target device.

Systems, methods, and media for causing an action to be performed on a user device are provided. In some implementations, the systems comprise: a first user device comprising at least one hardware processor that is configured to: detect a second user device in proximity to the first user device; receive a user input indicative of an action to be performed; determine a plurality of candidate devices that are capable of performing the action, wherein the plurality of candidate devices includes the second user device; determine a plurality of device types corresponding to the plurality of candidate devices; determine a plurality of priorities associated with the plurality of candidate devices based at least in part on the plurality of device types; select a target device from the plurality of candidate devices based at least in part on the plurality of priorities; and cause the action to be performed by the target device.

A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.

A computer-implemented method includes: receiving, by a computing device, an incoming telephone call from a caller; identifying, by the computing device, a telephone number associated with the telephone call; obtaining, by the computing device, contextual data based on the telephone number, predicting, by the computing device, one or more reasons for the telephone call based on the contextual data; and displaying, by the computing device, the one or more reasons for the telephone call.

A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.

A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.

A computer-implemented method is disclosed for integrating at least one first communication terminal assigned to a user as a preferred device in a static configuration of a communication system and/or for dynamically switching from a first communication terminal used as a preferred device to a second communication terminal as a preferred device for providing a one-number service using the preferred device, to which a one-number service number is assigned, wherein at least two communication terminals are statically assigned to the user and a preferred device is also dynamically assigned to the user through a virtual device. Also disclosed is communication system designed for this purpose.

A computer-implemented method is disclosed for integrating at least one rust communication terminal assigned to a user as a preferred device in a static configuration of a communication system and/or for dynamically switching from a first communication terminal used as a preferred device to a second communication terminal as a preferred device for providing a one-number service using the preferred device, to which a one-number service number is assigned, wherein at least two communication terminals are statically assigned to the user and a preferred device is also dynamically assigned to the user through a virtual device. Also communication system designed for this purpose.

An availability-based telephonic transmission/reception calling service method is provided for communicating with a person who has a different lifestyle or who may not be available at a specific call time. When a receiver inputs the receiver's characteristic information and reception/communication availability information into a server, the server acquires and sets the reception/communication availability information. An originator fetches contact information in a memory medium within a device or contact information to be displayed in a separate service on the Internet and selects a receiver. When the contact information of the selected receiver is stored on the server, the server acquires the receiver's reception/communication availability information and displays whether the receiver can receive a call on a screen of an originator's communication device. Thus, the originator can be notified of whether a receiver can receive a call before the originator makes a telephone call via a cellular phone network or the Internet.

A server can receive a plurality of records at a databases such that each record is associated with a phone call and includes at least one request generated based on a transcript of the phone call. The server can generate a training dataset based on the plurality of records. The server can further train a binary classification model using the training dataset. Next, the server can receive a live transcript of a phone call in progress. The server can generate at least one live request based on the live transcript using a natural language processing module of the server. The server can provide the at least one live request to the binary classification model as input to generate a prediction. Lastly, the server can transmit the prediction to an entity receiving the phone call in progress. The prediction can cause a transfer of the call to a chatbot.