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<titleInfo><title>An approach towards adaptive service composition in markets of composed services</title></titleInfo>





<name type="personal">
  <namePart type="given">Alexander</namePart>
  <namePart type="family">Jungmann</namePart>
  <role><roleTerm type="text">author</roleTerm> </role></name>
<name type="personal">
  <namePart type="given">Felix</namePart>
  <namePart type="family">Mohr</namePart>
  <role><roleTerm type="text">author</roleTerm> </role></name>







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  <identifier type="local">672</identifier>
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<abstract lang="eng">On-the-fly composition of service-based software solutions is still a challenging task. Even more challenges emerge when facing automatic service composition in markets of composed services for end users. In this paper, we focus on the functional discrepancy between “what a user wants” specified in terms of a request and “what a user gets” when executing a composed service. To meet the challenge of functional discrepancy, we propose the combination of existing symbolic composition approaches with machine learning techniques. We developed a learning recommendation system that expands the capabilities of existing composition algorithms to facilitate adaptivity and consequently reduces functional discrepancy. As a representative of symbolic techniques, an Artificial Intelligence planning based approach produces solutions that are correct with respect to formal specifications. Our learning recommendation system supports the symbolic approach in decision-making. Reinforcement Learning techniques enable the recommendation system to adjust its recommendation strategy over time based on user ratings. We implemented the proposed functionality in terms of a prototypical composition framework. Preliminary results from experiments conducted in the image processing domain illustrate the benefit of combining both complementary techniques.</abstract>

<originInfo><dateIssued encoding="w3cdtf">2015</dateIssued>
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<language><languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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<relatedItem type="host"><titleInfo><title>Journal of Internet Services and Applications 6(1)</title></titleInfo>
<part><extent unit="pages">1-18</extent>
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<bibliographicCitation>
<ieee>A. Jungmann and F. Mohr, “An approach towards adaptive service composition in markets of composed services,” &lt;i&gt;Journal of Internet Services and Applications 6(1)&lt;/i&gt;, pp. 1–18, 2015.</ieee>
<apa>Jungmann, A., &amp;#38; Mohr, F. (2015). An approach towards adaptive service composition in markets of composed services. &lt;i&gt;Journal of Internet Services and Applications 6(1)&lt;/i&gt;, 1–18.</apa>
<short>A. Jungmann, F. Mohr, Journal of Internet Services and Applications 6(1) (2015) 1–18.</short>
<chicago>Jungmann, Alexander, and Felix Mohr. “An Approach towards Adaptive Service Composition in Markets of Composed Services.” &lt;i&gt;Journal of Internet Services and Applications 6(1)&lt;/i&gt;, 2015, 1–18.</chicago>
<mla>Jungmann, Alexander, and Felix Mohr. “An Approach towards Adaptive Service Composition in Markets of Composed Services.” &lt;i&gt;Journal of Internet Services and Applications 6(1)&lt;/i&gt;, 2015, pp. 1–18.</mla>
<bibtex>@article{Jungmann_Mohr_2015, title={An approach towards adaptive service composition in markets of composed services}, journal={Journal of Internet Services and Applications 6(1)}, author={Jungmann, Alexander and Mohr, Felix}, year={2015}, pages={1–18} }</bibtex>
<ama>Jungmann A, Mohr F. An approach towards adaptive service composition in markets of composed services. &lt;i&gt;Journal of Internet Services and Applications 6(1)&lt;/i&gt;. Published online 2015:1-18.</ama>
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