Abstract:
Information Systems today record the execution of activities into event logs.
Process Mining is an area of research that deals with the study and analysis
of various business processes based on these event logs. These event logs also
record the performers of each of the activities. Mining social network using
this information, understanding work-flow management and deriving relationships
between actors based on different metrics viz. handover of task,
subcontract, etc. is what constitutes Organizational Mining. Metrics based
on Joint Activities and Metrics based on (possible) causality, commonly referred
to as Similar-Task Algorithm and Subcontract Algorithm forms the
basis of this paper. We present Cypher Query Language(Neo4j) and SQL
(Structured Query Language) implementations of Similar-Task and Subcontract
Algorithms. Graph Databases have shown to perform well in cases
where information follows linked structure and needs to query to depth(s)
of a hierarchical setup. We conduct an empirical study on a large real
world data set to compare the performance of Neo4j against MySQL. We
benchmark performance factors like query execution time, CPU usage and
disk/memory space usage when implementing Similar-task and Subcontract
algorithms in Cypher Query Language and SQL.
