Cloud based chat governance system based on behavioral patterns and situational-awareness

1. A computer-implemented method for cloud based intelligent chat governance, the computer-implemented method comprising:

analyzing, by an integrated server environment using a machine learning technique, an incoming message from a chat initiator based on recorded in a chat governance repository behavioral patterns of users of a chat session, relationship between a plurality of users, content of the incoming message, and metadata of the incoming message;

calculating a plurality of prioritization metrics of the incoming message based on a comparison of the analyzed message to a knowledge base using a generalized linear modeling analysis, wherein the knowledge base includes: behavioral tendencies of users of the incoming message, patterns of interaction of the users, and situational awareness of the users, wherein the patterns persist in a dynamic knowledge base system that learns, monitors, and stores, details of the behavioral patterns of the users, and updates the behavioral patterns of the users during the chat sessions, and wherein the situational awareness of the users comprises relative hierarchical positions of the users in an organization; and

in response to a determination that at least one of the plurality of prioritization metrics is greater than a threshold level:

transmitting the incoming message to a client interface of a chat receiver; and

analyzing a feedback and a past behavior of the chat initiator and the chat receiver, and storing the analyzed feedback in the chat governance repository.

2. The computer-implemented method of claim 1 , further comprises: receiving current or history feedback from the plurality of users to update the knowledge base.

3. The computer-implemented method of claim 1 , wherein content of the incoming message is analyzed with natural language process.

4. The computer-implemented method of claim 1 , further comprises: the first computer building a statistical model for calculating response time of the incoming message.

5. The computer-implemented method of claim 1 , wherein the content of the incoming message is based on discussed topics of the incoming message between the plurality of users.

6. The computer-implemented method of claim 1 , wherein the metadata of the incoming message is based on calendar or activity history of the incoming message.

7. A computer system for cloud based intelligent chat governance, the computer system comprising:

one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising:

program instructions to analyze, by an integrated server environment using a machine learning technique, an incoming message from a chat initiator based on recorded in a chat governance repository behavioral patterns of users of a chat session, relationship between a plurality of users, content of the incoming message, and metadata of the incoming message;

program instructions to calculate a plurality of prioritization metrics of the incoming message based on a comparison of the analyzed message to a knowledge base using a generalized linear modeling analysis, wherein the knowledge base includes: behavioral tendencies of users of the incoming message, patterns of interaction of the users, and situational awareness of the users, wherein the patterns persist in a dynamic knowledge base system that learns, monitors, and stores, details of the behavioral patterns of the users, and updates the behavioral patterns of the users during the chat sessions, and wherein the situational awareness of the users comprises relative hierarchical positions of the users in an organization; and

in response to a determination that at least one of the plurality of prioritization metrics is greater than a threshold level:

program instructions to transmit the incoming message to a client interface of a chat receiver; and

program instructions to analyze a feedback and a past behavior of the chat initiator and the chat receiver, and storing the analyzed feedback in the chat governance repository.

8. The computer system of claim 7 , further comprises:

program instructions to receive current or history feedback from the plurality of users to update the knowledge base.

9. The computer system of claim 7 , wherein the content of the incoming message is analyzed with natural language process.

10. The computer system of claim 7 , further comprises:

program instructions to build a statistical model for calculating response time of the incoming message.

11. The computer system of claim 7 , wherein the metadata of the incoming message is based on calendar or activity of history of the incoming message.

12. A computer program product for cloud based intelligent chat governance, the computer system comprising:

one or more computer-readable tangible storage devices and program instructions stored on at least one of the one or more storage devices, the program instructions comprising:

program instructions to analyze, by a machine learning technique, an incoming message based on: behavioral patterns of uses of a chat session, relationship between a plurality of users, content of the incoming message, and metadata of the incoming message;

program instructions to calculate a plurality of prioritization metrics of the incoming message based on a comparison of the analyzed message to a knowledge base using a generalized linear modeling analysis, wherein the knowledge base includes: behavioral tendencies of users of the incoming message, patterns of interaction of the users, and situational awareness of the users, wherein the patterns persist in a dynamic knowledge base system that learns, monitors, and stores, details of the behavioral patterns of the users, and updates the behavioral patterns of the users during the chat sessions, and wherein the situational awareness of the users comprises relative hierarchical positions of the users in an organization; and

in response to a determination that at least one of the plurality of prioritization metrics is greater than a threshold level:

program instructions to transmit the incoming message to a client interface of a chat receiver; and

program instructions to analyze a feedback and a past behavior of the chat initiator and the chat receiver, and storing the analyzed feedback in the chat governance repository.

13. The computer program product of claim 12 , further comprises:

program instructions to receive current or history feedback from the plurality of users to update the knowledge base.

14. The computer program product of claim 12 , wherein the content of the incoming message is analyzed with natural language process.

15. The computer program product of claim 12 , further comprises:

program instructions to build a statistical model for calculating response time of the incoming message.

16. The computer program product of claim 12 , wherein the metadata of the incoming message is based on calendar or activity of history of the incoming message.

17. The computer program product of claim 12 , wherein the content of the incoming message is based on discussed topics of the incoming message between the plurality of users.