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

• US 10,616,369 B1
• Filed: 04/04/2018
• Issued: 04/07/2020
• Est. Priority Date: 04/04/2018
• Status: Active Grant

• Current Assignee: Fuze, Inc. (8X8, Inc.)
• Original Assignee: Fuze, Inc. (8X8, Inc.)
• Inventors: d'Andrea, Turchese, DiNunzio, Alexander, Huang, Nancy Ng, Johnson, Keith
• Primary Examiner(s): Hlaing, Soe
• Application Number:
  US15/945,441
• Time in Patent Office: 734 Days
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 20/10 using kernel methods, e.g. support vector machines [SVM]
• CPC Class Codes: G06N 20/20 Ensemble learning
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06N 3/126 Evolutionary algorithms, e.g. genetic algorithms or genetic programming
• CPC Class Codes: G06N 5/01 Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 10/063112 Skill-based matching of a person or a group to a task
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting
• CPC Class Codes: H04L 12/1822 Conducting the conference, e.g. admission, detection, selection or grouping of participants, correlating users to one or more conference sessions, prioritising transmission
• CPC Class Codes: H04L 51/224 providing notification on incoming messages, e.g. pushed notifications of received messages
• CPC Class Codes: H04L 65/1069 Session establishment or de-establishment
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15
• CPC Class Codes: H04L 67/54 Presence management, e.g. monitoring or registration for receipt of user log-on information, or the connection status of the users
• CPC Class Codes: H04L 67/55 Push-based network services
• CPC Class Codes: H04L 67/60 Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources admission control or resource allocation H04L47/70

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.

Claims

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.