Semantic Annotation for Process Models: - Department of Computer ...

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Algorithm 1 Goal Annotation Algorithm for Case A
Require: weight parameters α and β
initialize values of weight f oractivityonto, weight f oractivityname, σ, τ as 0
onto = OD(av) {av is the activity to be annotated in goal annotation, and OD(av)
gets the domain ontological concept which was annotated to av in model annotation}
r = SR(av, onto) {SR(av, onto) gets the semantic relationship between av and onto}
for each target activity av ′ of a g in goal ontology do
if o equals av ′ then
if r is "same_as" then
σ = 1
else if r is "kind_of" then
σ = 0.8
else if r is "phase_of" then
σ = 0.5
end if
end if
weight f orativityonto = weight f oractivityonto+σ
if av.name equals av ′ .name by string match then
τ = 1
else if av.name partly equals av ′ .name by string match then
τ = 0.5
end if
weight f oractivityname = weight f oractivityname+τ
end for
return α ∗ weight f oractivityonto+β ∗ weight f oractivityname
Algorithm 2 Goal Annotation Algorithm for Case B.I
Require: weight parameters θ
initialize value of weight f oroutput as 0
Arrayout[] is a set of output associated with av {av is the activity to be annotated
in goal annotation. out[] is got from has_Output relationship}
for each output in out[] do
onto = OD(out) {OD(out) gets the domain ontological concept which was annotated
to output through mapped_to relationship}
for each target artifact a f ′ of a g in goal ontology do
if onto equals a f then
weight f oroutput = weight f oroutput+ 1
end if
end for
end for
return θ ∗ weight f oroutput