Analyses whether resources specialise in specific activities.
This metric can give an overview of which resources are performing certain activities more than others, and which resources are responsible for containing all knowledge or capabilities on one topic.
resource_specialisation(
log,
level = c("log", "activity", "resource"),
append = deprecated(),
append_column = NULL,
sort = TRUE,
eventlog = deprecated()
)resource_specialization(
log,
level = c("log", "activity", "resource"),
append = deprecated(),
append_column = NULL,
sort = TRUE,
eventlog = deprecated()
)
# S3 method for log
resource_specialisation(
log,
level = c("log", "activity", "resource"),
append = deprecated(),
append_column = NULL,
sort = TRUE,
eventlog = deprecated()
)
# S3 method for grouped_log
resource_specialisation(
log,
level = c("log", "activity", "resource"),
append = deprecated(),
append_column = NULL,
sort = TRUE,
eventlog = deprecated()
)
log
: Object of class log
or derivatives (grouped_log
, eventlog
, activitylog
, etc.).
character
(default "log"
): Level of granularity for the analysis: "log"
(default),
, "activity"
, or "resource"
. For more information, see vignette("metrics", "edeaR")
and 'Details' below.
logical
(default FALSE
) : The arguments
append
and append_column
have been deprecated in favour of augment
.
Indicating whether to append results to original log. Ignored when level is "log"
or "trace"
.
The arguments
append
and append_column
have been deprecated in favour of augment
.
Which of the output columns to append to log, if append = TRUE
. Default column depends on chosen level.
logical
(default TRUE
): Sort output on count. Only for levels with frequency count output.
resource_specialisation(log)
: Computes the resource specialisation for a log
.
resource_specialisation(grouped_log)
: Computes the resource specialisation for a grouped_log
.
Argument level
has the following options:
At "log"
level, this metric provides summary statistics on the number of distinct activities executed per resource.
On "activity"
level, this metric provides an overview of the absolute and relative number of different resources
executing this activity within the complete log. This will give insights into which activities resources are specialised in.
On "resource"
level, this metric shows the absolute and relative number of distinct activities that each resource executes.
Swennen, M. (2018). Using Event Log Knowledge to Support Operational Exellence Techniques (Doctoral dissertation). Hasselt University.
Other metrics:
activity_frequency()
,
activity_presence()
,
end_activities()
,
idle_time()
,
number_of_repetitions()
,
number_of_selfloops()
,
number_of_traces()
,
processing_time()
,
resource_frequency()
,
resource_involvement()
,
start_activities()
,
throughput_time()
,
trace_coverage()
,
trace_length()