System and method for distributing communication requests based on collaboration circle membership data using machine learning

Abstract

Various aspects of the subject technology related to systems, methods, and a machine readable storage medium for distributing communication requests based on collaboration circle membership data using machine learning. A system may be configured to receive a plurality of communication requests. Each communication request may include a request initiator and a request recipient. The system may process the plurality of communication requests to using one or more predictive models derived from a machine learning process to generate a communication request resolution for each of the plurality of communication requests. The system may forward a communication request notification to a request facilitator to implement the generated communication request resolution.

What is claimed is: 
     
       1. A computer-implemented method for distributing communication requests based on collaboration circle membership data using machine learning, the method comprising:
 receiving a plurality of communication requests, each communication request including a request initiator and a request recipient; 
 processing the plurality of communication requests using one or more predictive models derived from at least one machine learning process to generate a communication request resolution for each of the plurality of communication requests, wherein generating the communication request resolution further comprises:
 determining the request initiator and the request recipient, the request recipient being a member of one or more collaboration circles; 
 determining an availability status of the request recipient, wherein the availability status of the request recipient is included in one or more collaboration circle profiles associated with the request recipient; 
 determining a request facilitator associated with the request recipient based on the availability status of the request recipient; 
 determining one or more notification preferences associated with the request facilitator; 
 generating a communication request notification for the request facilitator based on the one or more notification preferences and based on historical communication patterns between the request facilitator and the request initiator; and 
 
 forwarding the communication request notification to the request facilitator to implement the generated communication request resolution. 
 
     
     
       2. The computer-implemented method of  claim 1 , wherein each of the plurality of communication requests comprises one of a telephone call, an email message, a text message, a video call, an audio note, a video collaboration session, a meeting invitation, or a push notification. 
     
     
       3. The computer-implemented method of  claim 1 , wherein the communication request notification comprises one or more of a telephone call, an email message, a text message, a video call, an audio note, a video collaboration session, a meeting invitation, or a push notification. 
     
     
       4. The computer-implemented method of  claim 1 , wherein determining the request initiator further comprises:
 determining if the request initiator is identifiable in one or more aggregated data sources based on a frequency or a recency of the request initiator's interaction with at least one of the one or more aggregated data sources. 
 
     
     
       5. The computer-implemented method of  claim 4 , wherein the one or more aggregated data sources include live or historical communication pattern data associated with a customer relationship management tool data source, a social network data source, a support ticketing platform data source, a customer support data source, a call history data source, a chat history data source, a calendar data source, a voicemail data source, or a caller ID name database. 
     
     
       6. The computer-implemented method of  claim 4 , wherein the one or more predictive models derived from at least one machine learning process are trained based on the one or more aggregated data sources. 
     
     
       7. The computer-implemented method of  claim 1 , wherein the one or more predictive models derived from at least one machine learning process include a first model associated with communication patterns of a request recipient and a second model associated with communication patterns of all request recipients within an organization or all request recipients within a collaboration circle. 
     
     
       8. The computer-implemented method of  claim 1 , further comprising determining the availability status for the request recipient based on a collaboration circle profile for at least one collaboration circle for which the request initiator or the request facilitator and the request recipient are members. 
     
     
       9. The computer-implemented method of  claim 1 , wherein the availability status of the request recipient is determined based on specific time frames identified in one or more collaboration circle profiles associated with the request recipient. 
     
     
       10. The computer-implemented method of  claim 1 , wherein the availability status for the request recipient is determined based on one or more predictive models derived from at least one machine learning process. 
     
     
       11. A system for distributing communication requests based on collaboration circle membership data using machine learning, the system comprising:
 a memory comprising instructions; and 
 one or more processors configured to execute instructions, which, when executed, cause the one or more processors to: 
 receive a plurality of communication requests, each communication request including a request initiator and a request recipient; 
 process the plurality of communication requests using one or more predictive models derived from at least one machine learning process to generate a communication request resolution for each of the plurality of communication requests, wherein generating the communication request resolution further comprises:
 determining the request initiator and the request recipient, the request recipient being a member of one or more collaboration circles; 
 
 determining an availability status of the request recipient, wherein the availability status of the request recipient is included in one or more collaboration circle profiles associated with the request recipient; 
 determining a request facilitator associated with the request recipient based on the availability status of the request recipient; 
 determining one or more notification preferences associated with the request facilitator; 
 generating a communication request notification for the request facilitator based on the one or more notification preferences and based on historical communication patterns between the request facilitator and the request initiator; and 
 forwarding the communication request notification to the request facilitator to implement the generated communication request resolution. 
 
     
     
       12. The system of  claim 11 , wherein each of the plurality of communication requests comprises one of a telephone call, an email, an instant message, a text message, a video call, an audio note, a video collaboration session, or a push notification. 
     
     
       13. The system of  claim 11 , wherein a communication request notification comprises one or more of a telephone call, an email, an instant message, a text message, a video call, an audio note, a video collaboration session, or a push notification. 
     
     
       14. The system of  claim 11 , wherein the one or more processors are further configured to execute instructions, which, when executed, cause the one or more processors to determine if the request initiator is identifiable in one or more aggregated data sources based on a frequency or a recency of the request initiator's interaction with at least one of the one or more aggregated data sources. 
     
     
       15. The system of  claim 14 , wherein the one or more aggregated data sources include live or historical communication pattern data associated with a customer relationship management tool data source, a social network data source, a support ticketing platform data source, a customer support data source, a call history data source, a chat history data source, a calendar data source, a voicemail data source, or a caller ID name database. 
     
     
       16. The system of  claim 14 , wherein the one or more predictive models derived from at least one machine learning process are trained based on the one or more aggregated data sources. 
     
     
       17. The system of  claim 11 , wherein the one or more predictive models derived from at least one machine learning process include a first model associated with request recipient communication patterns and a second model associated with collaboration circle member communication patterns. 
     
     
       18. The system of  claim 11 , wherein the one or more processors are further configured to execute instructions, which, when executed, cause the one or more processors to determine the availability status for the request recipient based on a collaboration circle profile for at least one collaboration circle for which the request initiator or the request facilitator and the request recipient are members. 
     
     
       19. The system of  claim 11 , wherein the availability status for the request recipient is determined based on one or more predictive models derived from at least one machine learning process. 
     
     
       20. A non-transitory machine readable storage medium containing program instructions for distributing communication requests based on collaboration circle membership data using machine learning, the program instructions executable by one or more processors to perform operations comprising:
 receiving a plurality of communication requests, each communication request including a request initiator and a request recipient; 
 processing the plurality of communication requests using one or more predictive models derived from at least one machine learning process to generate a communication request resolution for each of the plurality of communication requests, wherein generating the communication request resolution further comprises: 
 determining the request initiator and the request recipient, the request recipient being a member of one or more collaboration circles; 
 determining an availability status of the request recipient, wherein the availability status of the request recipient is included in one or more collaboration circle profiles associated with the request recipient; 
 determining a request facilitator associated with the request recipient based on the availability status of the request recipient; 
 determining one or more notification preferences associated with the request facilitator; 
 generating a communication request notification for the request facilitator based on the one or more notification preferences and based on historical communication patterns between the request facilitator and the request initiator; and 
 forwarding the communication request notification to the request facilitator to implement the generated communication request resolution. 
 
     
     
       21. An apparatus comprising:
 a set of one or more servers, including one or more processors and communications circuitry to provide a communications platform, to provide communications services and to receive a plurality of communication requests, each communication request involving a request recipient corresponding to one or more collaboration circles and further involving a request initiator;   the one or more processors:
 to use a machine learning process to train one or more predictive models based on an aggregation of data corresponding to historical communications involving the request initiator and, in response, to generate a communication request resolution corresponding to the request recipient being associated with the one or more collaboration circles and to an availability status of the request recipient; and 
 to generate a communication request notification based on historical communication patterns between a request facilitator and the request initiator; and 
   the communications circuitry to, for each of the plurality of communication requests, send the communication request notification to the request facilitator, wherein the communication request notification is processed based on one or more notification preferences associated with the request facilitator, and the machine learning process is to train one or more predictive models based on patterns identifiable from the aggregation of data.    
     
     
       22. The apparatus of  claim 21 , wherein at least some of the historical communications are derived from the communications services provided by the communications platform.  
     
     
       23. The apparatus of  claim 21 , wherein the set of one or more servers includes a plurality of servers to provide the communications platform as a cloud-computing server in which the plurality of servers is communicatively interconnected by a communication network.  
     
     
       24. The apparatus of  claim 21 , wherein the communications platform is implemented to provide and support the communications services as PaaS (platform-as-a-service) type services.