Visualization controls
Minimum probability:
0.1
Simulation
Nr. Clusters:
1
Markov Chain Application Analysis
Minimum probability:
0.1
Nr. Clusters:
1
Made by Gilles Vandewiele (IDLab) in collaboration with Jeroen Stragier (MICT). Both are from Universiteit Gent -- imec.
The uploaded file has to be Comma-Separated Values (CSV) and must contain one of the sets of columns listed below. Moreover, these column names should be present on the first line in the CSV-file, in the same order.
from,to:
the most simple format which just lists the different transitions. With this format, sequence clustering and user action simulations are not possible, since there is no notion of sessions. An example is the following snippet:
from,to A,B B,C C,D A,C B,C A,B
from,to,session_id,timestamp:
The simple format, extended with a identifier for each user session and a time when the action was made. A session is defined as all the actions a user made from opening the application until closing it. This allows us to introduce a start- and exit- state in the markov chain. Moreover, sequence clustering and simulations of user actions are also possible. An example is the following snippet:
from,to,session_id,timestamp A,B,1,01/01/2018 15:00 B,C,1,01/01/2018 15:02 C,D,1,01/01/2018 15:03 A,C,3,01/01/2018 16:00 B,C,2,01/01/2018 17:05 A,B,2,01/01/2018 17:00
There is one special case which cannot be defined through this format: namely the sessions with only action. These can be defined by leaving to empty (A,,4,01/01/2018 15:00)
Everything you see is being performed client-side, this means that the uploaded data does never leave your computer!