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Statements

Subject Item
n2:RIV%2F67985807%3A_____%2F10%3A00359201%21RIV13-GA0-67985807
rdf:type
skos:Concept n20:Vysledek
dcterms:description
Majority of the existing approaches to service composition, including the widely popular planning based techniques, are not able to automatically compose practical workflows that include complex repetitive behaviors (loops), taking into account possibility of failures and nondeterminism of web service execution results. In this work, we present a learning based approach for composing task specific workflows. We present an approach for learning task specific web service compositions from a very small number of observations (one or more) of example service execution sequences (traces) that solve a given goal. The workflows learned by this approach generalize to the tasks justified by the observed execution trace. The generalization captures the repetitive executions of service sequences, conditional branching executions, and repetitions and branching resulting from failures. We evaluate the approach on a complex web services application involving arbitrary number of repetitive executions and failed executions. Majority of the existing approaches to service composition, including the widely popular planning based techniques, are not able to automatically compose practical workflows that include complex repetitive behaviors (loops), taking into account possibility of failures and nondeterminism of web service execution results. In this work, we present a learning based approach for composing task specific workflows. We present an approach for learning task specific web service compositions from a very small number of observations (one or more) of example service execution sequences (traces) that solve a given goal. The workflows learned by this approach generalize to the tasks justified by the observed execution trace. The generalization captures the repetitive executions of service sequences, conditional branching executions, and repetitions and branching resulting from failures. We evaluate the approach on a complex web services application involving arbitrary number of repetitive executions and failed executions.
dcterms:title
Learning Task Specific Web Services Compositions with Loops and Conditional Branches from Example Executions Learning Task Specific Web Services Compositions with Loops and Conditional Branches from Example Executions
skos:prefLabel
Learning Task Specific Web Services Compositions with Loops and Conditional Branches from Example Executions Learning Task Specific Web Services Compositions with Loops and Conditional Branches from Example Executions
skos:notation
RIV/67985807:_____/10:00359201!RIV13-GA0-67985807
n3:aktivita
n11:Z n11:P
n3:aktivity
P(GPP202/10/P604), P(ME08095), Z(AV0Z10300504)
n3:dodaniDat
n9:2013
n3:domaciTvurceVysledku
n13:7516983
n3:druhVysledku
n19:D
n3:duvernostUdaju
n14:S
n3:entitaPredkladatele
n4:predkladatel
n3:idSjednocenehoVysledku
268091
n3:idVysledku
RIV/67985807:_____/10:00359201
n3:jazykVysledku
n21:eng
n3:klicovaSlova
learning by demonstration; plan learning; task specific plan learning; web services; workflow learning
n3:klicoveSlovo
n15:plan%20learning n15:workflow%20learning n15:web%20services n15:task%20specific%20plan%20learning n15:learning%20by%20demonstration
n3:kontrolniKodProRIV
[C2BAA44E7629]
n3:mistoKonaniAkce
Toronto
n3:mistoVydani
Los Alamitos
n3:nazevZdroje
Web Intelligence and Intelligent Agent Technology
n3:obor
n17:IN
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
3
n3:projekt
n5:GPP202%2F10%2FP604 n5:ME08095
n3:rokUplatneniVysledku
n9:2010
n3:tvurceVysledku
Veloso, M. Vaculín, Roman Veeraraghavan, H.
n3:typAkce
n8:WRD
n3:zahajeniAkce
2010-08-31+02:00
n3:zamer
n22:AV0Z10300504
s:numberOfPages
8
n10:doi
10.1109/WI-IAT.2010.292
n16:hasPublisher
IEEE Computer Society
n18:isbn
978-0-7695-4191-4