![](bg9.png)
preferences. The algorithm either provides a first cor-
relation key set that meets quality or returns a sorted
list along with the respective conversations sets.
Our evaluation showed that despite using invari-
ants and quality attributes, Algorithm 1 may still re-
turn several correlation key sets. In this case, the user
has to choose one set with which conversations are
finally extracted. We intend to reduce the need for
supervision and increase precision by improving our
approach with a decision-making algorithm. The lat-
ter will compute correlation key set scores, choose the
most appropriate set, and finally, will automatically
return one conversation set.
ACKNOWLEDGEMENT
Research supported by the French Project VASOC
(Auvergne-Rh
ˆ
one-Alpes Region) https://vasoc.limos.
fr/.
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