DOMAIN EXPERT PREDICTOR
Disclosed are various approaches for predicting a domain expert. In one such embodiment, application usage data corresponding to conversations between users of a collaboration messaging service on a particular topic is obtained and used to generate a knowledge graph representing the users involved in the conversations on the particular topic. Thus, based on the knowledge graph, at least one user can be identified as a domain expert for the particular topic, wherein the at least one user is represented in the knowledge graph.
1 . An expert prediction system comprising:
at least one computing device;
at least one application executed by the at least one computing device, wherein the at least one application causes the at least one computing device to at least:
obtain application usage data corresponding to conversations between users of a collaboration messaging service on a particular topic;
generate from the application usage data a knowledge graph representing the users involved in the conversations on the particular topic;
obtain a request to provide a domain expert for the particular topic, the request received from a front-end interface to the at least one application; and
based on the knowledge graph, provide at least one user as a domain expert to the front-end interface, wherein the at least one user is represented in the knowledge graph.
2 . The system of claim 1 , wherein the front-end interface comprises a chatbot client.
3 . The system of claim 1 , wherein the application usage data is obtained from at least one of a management service or an identity manager, the management service remotely managing a client device associated with the at least one user user and the identity manager comprising a single sign-on service associated with the at least one user.
4 . The system of claim 3 , wherein application usage data comprises data measured by a management component running on a client device associated with the at least one user, wherein the management component reports application usage to the management service.
5 . The system of claim 1 , wherein the application usage data comprises specific keywords included in the conversations between the users.
6 . The system of claim 1 , wherein the application usage data comprises response times of the users in conversing about the particular topic.
7 . The system of claim 1 , wherein the at least one application causes the at least one computing device to at least:
categorize the users represented in the knowledge graph as an expert or as a practitioner for the particular topic.
8 . The system of claim 1 , wherein the request further specifies a particular group of users, wherein the knowledge graph only represents users that are members of the particular group of users.
9 . A non-transitory computer-readable medium comprising machine-readable instructions, wherein the instructions, when executed by at least one processor, cause a computing device to at least:
obtain application usage data corresponding to conversations between users of a collaboration messaging service on a particular topic;
generate from the application usage data a knowledge graph representing a team of users that are involved in the conversations on the particular topic;
obtain a request to provide a domain expert for the particular topic within the team of users from a client device; and
based on the knowledge graph for the team of users, provide at least one user as a domain expert to the client device, wherein the at least one user is represented in the knowledge graph.
10 . The non-transitory computer-readable medium of claim 9 , wherein the application usage data is obtained from at least one of a management service or an identity manager, the management service remotely managing the client device associated with the at least one user and the identity manager comprising a single sign-on service associated with the at least one user.
11 . The non-transitory computer-readable medium of claim 10 , wherein application usage data comprises data measured by a management component running on the client device associated with the at least one user, wherein the management component reports application usage to the management service.
12 . The non-transitory computer-readable medium of claim 9 , wherein the application usage data comprises specific keywords included in the conversations between the users.
13 . The non-transitory computer-readable medium of claim 9 , wherein the application usage data comprises response times of the users in conversing about the particular topic.
14 . The non-transitory computer-readable medium of claim 9 , wherein the instructions, when executed by at least one processor, cause a computing device to at least:
categorize the users represented in the knowledge graph as an expert or as a practitioner for the particular topic.
15 . A method comprising:
obtaining, via a computing device, application usage data corresponding to conversations between users of a collaboration messaging service on a particular topic;
generating, via the computing device, from the application usage data a knowledge graph representing the users involved in the conversations on the particular topic;
obtaining, via the computing device, a request to provide a domain expert for the particular topic; and
based on the knowledge graph, providing, via the computing device, at least one user as a domain expert to a client device, wherein the at least one user is represented in the knowledge graph.
16 . The method of claim 15 , wherein the application usage data is obtained from at least one of a management service or an identity manager, the management service remotely managing the client device associated with the at least one user and the identity manager comprising a single sign-on service associated with the at least one user.
17 . The method of claim 16 , wherein application usage data comprises data measured by a management component running on the client device associated with the at least one user, wherein the management component reports application usage to the management service.
18 . The method of claim 15 , wherein the application usage data comprises specific keywords included in the conversations between the users and response times of the users in conversing about the particular topic.
19 . The method of claim 15 , further comprising categorizing, via the computing device, the users represented in the knowledge graph as an expert or as a practitioner for the particular topic.
20 . The method of claim 15 , wherein the request further specifies a particular team of users, wherein the knowledge graph only represents users that are members of the particular team of users.