  In cloud systems, incidents are potential threats to customer satisfaction
and business revenue. When customers are affected by incidents, they often
request customer support service (CSS) from the cloud provider by submitting a
support ticket. Many tickets could be duplicate as they are reported in a
distributed and uncoordinated manner. Thus, aggregating such duplicate tickets
is essential for efficient ticket management. Previous studies mainly rely on
tickets' textual similarity to detect duplication; however, duplicate tickets
in a cloud system could carry semantically different descriptions due to the
complex service dependency of the cloud system. To tackle this problem, we
propose iPACK, an incident-aware method for aggregating duplicate tickets by
fusing the failure information between the customer side (i.e., tickets) and
the cloud side (i.e., incidents). We extensively evaluate iPACK on three
datasets collected from the production environment of a large-scale cloud
platform, Azure. The experimental results show that iPACK can precisely and
comprehensively aggregate duplicate tickets, achieving an F1 score of 0.871 ~
0.935 and outperforming state-of-the-art methods by 12.4% ~ 31.2%.
