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I am working on a problem in which the events are meetings. The meetings happen at a given place, starting time, duration, and has two or more attendees. The are certain periodic meetings (weekly, monthly, etc) with the same participants, usually in the same location and time.
Being new to this community, I am interested in any modeling recommendations for this type of problem. I understand that there is no way to represent geospatial information, so I assume that the meeting names need to include the location.
The objective is to detect the recurring meetings, or the sequence of meetings of a given individual, etc.
Is this a typical process mining problem? Are there papers that would suggest ways to model this?
There is a lot of noise in the data (random meetings). Are there algorithms that are better or worse for this type of problem.
Thanks in advance for any suggestions.
Post edited by JBuijs on
Research Scientist II
Knowledge Based Systems, Inc.