METHODS AND SYSTEMS FOR ASSOCIATING A TEAM WITH A MEETING
A method for associating a meeting invitation with a team includes receiving a meeting invitation from an email system comprising names of invitees and receiving team information from a team system comprising names of team members and team topics. Using a trained machine learning model, a match metric representing similarity between teams and the meeting invitation is calculated. Calculating the match metric includes determining an attendee score based on invitees who are team members and a topic score based on comparison between a meeting topic and team topics. The match metric is based on the attendee score and topic score. The trained machine learning model uses names of invitees, names of team members, and team topics. The method further includes adding to the meeting invitation a link to the team with the highest match metric.
1 . A method for associating a meeting invitation with a team, the method comprising:
receiving a meeting invitation from an email system, wherein the meeting invitation comprises names of a plurality of invitees;
receiving team information from a team system, wherein the team information comprises names of team members for a plurality of teams and team topics of the plurality of teams;
using a trained machine learning model, calculating a match metric representing match similarity between teams and the meeting invitation, wherein calculating the match metric comprises:
calculating an attendee score based on a number of the invitees that are members of each team;
calculating a topic score based on a comparison between a meeting topic and the team topics of the plurality of teams; and
calculating the match metric based on the attendee score and the topic score;
wherein the trained machine learning model uses the names of the invitees, the names of team members of the plurality of teams, and the team topics of the plurality of teams; and
causing to add to the meeting invitation a link to a team from the plurality of teams with the highest match metric.
2 . The method of claim 1 , wherein calculating the match metric comprises calculating a weighted average of the attendee score and the topic score.
3 . The method of claim 1 , in response to determining that the highest match metric is below a threshold value, creating a new team comprising the plurality of invitees as team members.
4 . The method of claim 1 , further comprising inviting a member of the team with the highest match metric to the meeting when the member is not identified as one of the plurality of invitees.
5 . The method of claim 1 , wherein the match metric is further based on a date and time of the meeting.
6 . The method of claim 1 , wherein causing to add to the meeting invitation the link comprises providing the plurality of invitees with the link to an interface for the team with the highest match metric.
7 . The method of claim 1 , wherein calculating the match metric further comprises analyzing historical communication data using a natural language processing algorithm to determine the team topics.
8 . A non-transitory, computer-readable medium, storing instructions for managing real-time communication sessions that, when executed by a processor, cause:
receiving a meeting invitation from an email system, wherein the meeting invitation comprises names of a plurality of invitees;
receiving team information from a team system, wherein the team information comprises names of team members for a plurality of teams and team topics of the plurality of teams;
using a trained machine learning model, calculating a match metric representing match similarity between teams and the meeting invitation 1 , wherein calculating the match metric comprises:
calculating an attendee score based on a number of the invitees that are members of each team;
calculating a topic score based on a comparison between a meeting topic and the team topics of the plurality of teams; and
calculating the match metric based on the attendee score and the topic score;
wherein the trained machine learning model uses the names of the invitees, the names of team members of the plurality of teams, and the team topics of the plurality of teams; and
causing to add to the meeting invitation a link to a team from the plurality of teams with the highest match metric.
9 . The non-transitory, computer-readable medium of claim 8 , wherein calculating the match metric comprises calculating a weighted average of the attendee score and the topic score.
10 . The non-transitory, computer-readable medium of claim 8 , wherein the instructions further comprise: in response to determining that the highest match metric is below a threshold value, creating a new team comprising the plurality of invitees as team members.
11 . The non-transitory, computer-readable medium of claim 8 , wherein the instructions further comprise inviting a member of the team with the highest match metric to the meeting when the member is not identified as one of the plurality of invitees.
12 . The non-transitory, computer-readable medium of claim 8 , wherein the match metric is further based on a date and time of the meeting.
13 . The non-transitory, computer-readable medium of claim 8 , wherein causing to add to the meeting invitation the link comprises providing the plurality of invitees with the link to an interface for the team with the highest match metric.
14 . The non-transitory, computer-readable medium of claim 8 , wherein calculating the match metric further comprises analyzing historical communication data using a natural language processing algorithm to determine the team topics.
15 . A system for associating a meeting invitation with a team, comprising:
a processor;
a memory operatively connected to the processor and storing instructions for managing real-time communication sessions, the instructions, when executed by the processor, cause:
receiving a meeting invitation from an email system, wherein the meeting invitation comprises names of a plurality of invitees;
receiving team information from a team system, wherein the team information comprises names of team members for a plurality of teams and team topics of the plurality of teams;
using a trained machine learning model, calculating a match metric representing match similarity between teams and the meeting invitation, wherein calculating the match metric comprises:
calculating an attendee score based on a number of the invitees that are members of each team;
calculating a topic score based on a comparison between a meeting topic and the team topics of the plurality of teams; and
calculating the match metric based on the attendee score and the topic score;
wherein the trained machine learning model uses the names of the invitees, the names of team members of the plurality of teams, and the team topics of the plurality of teams; and
causing to add to the meeting invitation a link to a team from the plurality of teams with the highest match metric.
16 . The system of claim 15 , wherein calculating the match metric comprises calculating a weighted average of the attendee score and the topic score.
17 . The system of claim 15 , wherein the instructions further comprise: in response to determining that the highest match metric is below a threshold value, creating a new team comprising the plurality of invitees as team members.
18 . The system of claim 15 , wherein the instructions further comprise inviting a member of the team with the highest match metric to the meeting when the member is not identified as one of the plurality of invitees.
19 . The system of claim 15 , wherein the match metric is further based on a date and time of the meeting.
20 . The system of claim 15 , wherein calculating the match metric further comprises analyzing historical communication data using a natural language processing algorithm to determine the team topics.