Paper Info
Title
Using graph aggregation for service interaction message correlation
Abstract
Discovering the behavior of services and their interactions in an enterprise requires the ability to correlate service interaction messages into process instances. The service interaction logic (or process model) is then discovered from the set of process instances that are the result of a given way of correlating messages. However, sometimes, the Correlation Conditions (CC) allowing to identify correlations of messages from a service interaction log are not known. In such cases, and with a large number of message's correlator attributes, we are facing a large space of possible ways messages may be correlated which makes identifying process instances difficult. In this paper, we propose an approach based on message indexation and aggregation to generate a size-efficient Aggregated Correlation Graph (ACG) that exhibits all the ways messages correlate in a service interaction log not only for disparate pairs of messages but also for sequences of messages corresponding to process instances. Adapted filtering techniques based on user defined heuristics are then applied on such a graph to help the analysts efficiently identify the most frequently executed processes from their sequences of CCs. The approach has been implemented and experiments show its effectiveness to identify relevant sequences of CCs from large service interaction logs.
Year
DOI
Venue
2011
10.1007/978-3-642-21640-4_47
CA(i)SE
Keywords
Field
DocType
large space,process model,process instance,service interaction message,correlation graph,correlation conditions,service interaction log,large number,service interaction logic,graph aggregation,large service interaction log,service interaction message correlation,soa,aggregation,correlation,process mining
Data mining,Graph,Indexation,Computer science,Filter (signal processing),Heuristics,Correlation,Correlation graph,Process mining
Conference
Citations 
PageRank 
References 
2
0.37
11
Authors
3
Name
Order
Citations
PageRank
Adnene Guabtni11188.61
Hamid Reza Motahari-Nezhad244724.70
Boualem Benatallah36174494.38