Meeting creation based on NLP analysis of contextual information associated with the meeting
One example method of operation may include identifying a proposed meeting summary, processing proposed meeting summary content of the proposed meeting summary to identify topics to apply to a meeting, creating the meeting to include meeting time intervals, assigning one or more of the topics to one or more of the meeting time intervals, identifying profiles of user accounts matching one or more of the topics, assigning the user accounts, with profiles matching one or more of the topics, to one or more of the meeting time intervals with assigned ones of the topics which match the profiles of the user accounts, transmitting meeting invites to the user accounts, and initiating the meeting at a scheduled time.
1. A method comprising:
receiving, via a server, content from an electronic media channel including one or more of an email, a text message, and a transcript of a telephone call;
determining, via a natural language processing (NLP) engine, one or more keywords associated with the meeting within the received content and generating an NLP summary associated with the meeting including the one or more keywords;
determining, via the server, to automatically schedule an online meeting based on the one or more keywords determined via the NLP engine;
identifying a plurality of topics for the online meeting based on an analysis of the content;
identifying attendees of the online meeting based on content included in NLP summaries recognized from user profiles of the identified attendees compared to the generated NLP summary associated with the meeting;
automatically transmitting, from the server, meeting invitations to user devices of the identified attendees;
initiating the online meeting at a scheduled time;
identifying whether each attendee has satisfied a topic obligation based on an amount of time that each attendee was active during a corresponding meeting time interval; and
predicting a need for a future meeting based on satisfaction of the topic obligations.
2. The method of claim 1 , further comprising:
parsing words and phrases from the content;
responsive to the parsing of the words and phrases, determining a number of occurrences of related words and phrases; and
creating the plurality of topics based on the number of occurrences of related words and phrases.
3. The method of claim 1 , further comprising:
parsing the user profiles to identify keywords of interest;
comparing the keywords of interest to the plurality of topics to generate confidence values based on a relevancy of the keywords of interest to the plurality of topics; and
assigning a user profile to the online meeting which has a confidence value above a threshold confidence level.
4. The method of claim 1 , further comprising:
determining during the online meeting that a new online meeting is going to begin within a threshold period of time; and
transmitting meeting invitations to attendees that are assigned to the new online meeting.
5. The method of claim 4 , further comprising:
determining at the end of the new online meeting that one or more attendees that were sent a meeting invitation to participate in the new online meeting did not participate in the new online meeting.
6. The method of claim 5 , wherein after the online meeting is completed, the method further comprises:
transmitting one or more of textual, audio and video information corresponding to the new online meeting to user devices of the one or more attendees that did not participate in the new online meeting.
7. An apparatus comprising:
a processor configured to:
receive, via a server, content from an electronic media channel including one or more of an email, a text message, and a transcript of a telephone call;
determine, via a natural language processing (NLP) engine, one or more keywords associated with the meeting within the received content and generating an NLP summary associated with the meeting including the one or more keywords;
determine, via the server, to automatically schedule an online meeting based on the one or more keywords determined via the NLP engine;
identify a plurality of topics for the online meeting based on an analysis of the content,
identify attendees of the online meeting based on content included in NLP summaries recognized from user profiles of the identified attendees compared to the generated NLP summary associated with the meeting,
automatically transmit, from the server, meeting invitations to user devices of the identified attendees,
initiate the online meeting at a scheduled time,
identify whether each attendee has satisfied a topic obligation based on an amount of time that each attendee was active during a corresponding meeting time interval, and
predict a need for a future meeting based on satisfaction of the topic obligations.
8. The apparatus of claim 7 , wherein the processor is further configured to:
parse words and phrases from the content;
responsive to the parses words and phrases, determine a number of occurrences of related words and phrases; and
create the plurality of topics based on the number of occurrences of related words and phrases.
9. The apparatus of claim 7 , wherein the processor is further configured to:
parse the user profiles to identify keywords of interest;
compare the keywords of interest to the plurality of topics to generate confidence values based on a relevancy of the keywords of interest to the plurality of topics; and
assign a user profile to the online meeting which has a confidence value above a threshold confidence level.
10. The apparatus of claim 7 , wherein the processor is further configured to:
determine during the online meeting that a new online meeting is going to begin within a threshold period of time;
transmit meeting invitations to attendees that are assigned to the new online meeting.
11. The apparatus of claim 10 , wherein the processor is further configured to:
determine at the end of the new online meeting that one or more attendees that were sent a meeting invitation to participate in the new online meeting did not participate in the new online meeting.
12. The apparatus of claim 11 , wherein after the online meeting is completed, the processor is further configured to:
transmit one or more of textual, audio and video information corresponding to the new online meeting to user devices of the one or more attendees that were sent the meeting invitation to participate in the new online meeting and did not participate in the new online meeting.
13. A non-transitory computer readable storage medium configured to store one or more instructions that when executed by a processor cause the processor to perform:
receiving, via a server, content from an electronic media channel including one or more of an email, a text message, and a transcript of a telephone call;
determining, via a natural language processing (NLP) engine, one or more keywords associated with the meeting within the received content and generating an NLP summary associated with the meeting including the one or more keywords;
determining, via the server, to automatically schedule an online meeting based on the one or more keywords determined via the NLP engine;
identifying a plurality of topics for the online meeting based on an analysis of the content;
identifying attendees of the online meeting based on content included in NLP summaries recognized from user profiles of the identified attendees compared to the generated NLP summary associated with the meeting;
automatically transmitting, from the server, meeting invitations to user devices of the identified attendees;
initiating the online meeting at a scheduled time; and
identifying whether each attendee has satisfied a topic obligation based on an amount of time that each attendee was active during a corresponding specific time interval.
14. The non-transitory computer readable storage medium of claim 13 , wherein the one or more instructions further cause the processor to perform:
parsing words and phrases from the content;
responsive to the parsing of the words and phrases, determining a number of occurrences of related words and phrases; and
creating the plurality of topics based on the number of occurrences of related words and phrases.
15. The non-transitory computer readable storage medium of claim 13 , wherein the one or more instructions further cause the processor to perform:
parsing the user profiles to identify keywords of interest;
comparing the keywords of interest to the plurality of topics to generate confidence values based on a relevancy of the keywords of interest to the plurality of topics; and
assigning user profiles to the online meeting which have a confidence value above a threshold confidence level.
16. The non-transitory computer readable storage medium of claim 13 , wherein the one or more instructions further cause the processor to perform:
determining during the meeting that a new online meeting is going to begin within a threshold period of time; and
transmitting meeting invitations to attendees that are assigned to the new online meeting.
17. The non-transitory computer readable storage medium of claim 16 , wherein the one or more instructions further cause the processor to perform:
determining at the end of the new online meeting that one or more attendees that were sent a meeting invitation to participate in the new online meeting did not participate in the new online meeting, and
transmitting one or more of textual, audio and video information corresponding to the new online meeting to user devices of the one or more attendees that were sent the meeting invitation to participate in the new online meeting and did not participate in the new online meeting.