Systems and methods for inferring intent to opt-out of communications
A processing server assists in selectively removing or opting-out a client device from further communications. The processing server includes a hardware processor, and memory storing computer instructions that when executed perform transmitting a message to an entity, indicating directions to opt-out of receiving further communications, receiving, in response to the transmitting of the message, a reply, from the entity, inferring an intent of the reply pertaining to opting-out of receiving communications, and selectively terminating the communications based on the inferred intent.
1. A server system configured to infer opt-out instructions in a reply message from a user, the server system comprising:
one or more hardware processors; and
memory storing computer instructions, the computer instructions when executed by the one or more hardware processors configured to perform:
receiving a reply from the user of a client device, in response to a communication sent to the client device;
evaluating sentiment and context of the reply to infer intent whether to opt-out of receiving future communications and to generate a confidence score associated with the intent, the evaluating using a computer model;
selectively instructing to terminate the future communications based on the inferred intent and the confidence score;
receiving feedback, the feedback including an instruction to opt back in after instructing to terminate the future communications or including an adjustment of the confidence score; and
training the computer model based on the feedback.
2. The server system of claim 1 , wherein the sentiment is based on an existence or an absence of profanity within the reply.
3. The server system of claim 1 , wherein the sentiment is based on historical behavior associated with the user of the client device.
4. The server system of claim 3 , wherein the historical behavior is based on a frequency of opting back in following the instructing to terminate the future communications.
5. The server system of claim 1 , wherein the context is based on the communication sent to the client device.
6. The server system of claim 1 , wherein the computer model is generated by a trained machine learning component.
7. The server system of claim 1 , wherein the evaluating the sentiment and the context of the reply includes evaluating media components within the reply.
8. The server system of claim 1 , wherein the computer instructions, when executed by the one or more hardware processors, are configured to perform adjusting a frequency of the future communications based on an ambivalent confidence score.
9. A processor-based method of inferring opt-out instructions in a reply message from a user, the method comprising:
receiving a reply from the user of a client device, in response to a communication sent to the client device;
evaluating sentiment and context of the reply to infer intent whether to opt-out of receiving future communications and to generate a confidence score associated with the intent, the evaluating using a computer model;
selectively instructing to terminate the future communications based on the inferred intent and the confidence score;
receiving feedback, the feedback including an instruction to opt back in after instructing to terminate the future communications or including an adjustment of the confidence score; and
training the computer model based on the feedback.
10. The processor-based method of claim 9 , wherein the sentiment is based on an existence or an absence of profanity within the reply.
11. The processor-based method of claim 9 , wherein the sentiment is based on historical behavior associated with the user of the client device.
12. The processor-based method of claim 11 , wherein the historical behavior is based on a frequency of opting back in following the instructing to terminate the future communications.
13. The processor-based method of claim 9 , wherein the context is based on the communication sent to the client device.
14. The processor-based method of claim 9 , wherein the computer model is generated by a trained machine learning component.
15. The processor-based method of claim 9 , wherein the evaluating the sentiment and the context of the reply includes evaluating media components within the reply.
16. The processor-based method of claim 9 , further comprising adjusting a frequency of the future communications based on an ambivalent confidence score.