{"type":"conference","date_updated":"2022-01-06T07:01:06Z","publication":"Proceedings of the 10th World Congress on Services (SERVICES)","language":[{"iso":"eng"}],"title":"Combining Automatic Service Composition with Adaptive Service Recommendation for Dynamic Markets of Services","_id":"447","department":[{"_id":"355"}],"user_id":"477","citation":{"ieee":"A. Jungmann, F. Mohr, and B. Kleinjohann, “Combining Automatic Service Composition with Adaptive Service Recommendation for Dynamic Markets of Services,” in <i>Proceedings of the 10th World Congress on Services (SERVICES)</i>, 2014, pp. 346–353.","mla":"Jungmann, Alexander, et al. “Combining Automatic Service Composition with Adaptive Service Recommendation for Dynamic Markets of Services.” <i>Proceedings of the 10th World Congress on Services (SERVICES)</i>, 2014, pp. 346–53, doi:<a href=\"https://doi.org/10.1109/SERVICES.2014.68\">10.1109/SERVICES.2014.68</a>.","ama":"Jungmann A, Mohr F, Kleinjohann B. Combining Automatic Service Composition with Adaptive Service Recommendation for Dynamic Markets of Services. In: <i>Proceedings of the 10th World Congress on Services (SERVICES)</i>. ; 2014:346-353. doi:<a href=\"https://doi.org/10.1109/SERVICES.2014.68\">10.1109/SERVICES.2014.68</a>","bibtex":"@inproceedings{Jungmann_Mohr_Kleinjohann_2014, title={Combining Automatic Service Composition with Adaptive Service Recommendation for Dynamic Markets of Services}, DOI={<a href=\"https://doi.org/10.1109/SERVICES.2014.68\">10.1109/SERVICES.2014.68</a>}, booktitle={Proceedings of the 10th World Congress on Services (SERVICES)}, author={Jungmann, Alexander and Mohr, Felix and Kleinjohann, Bernd}, year={2014}, pages={346–353} }","chicago":"Jungmann, Alexander, Felix Mohr, and Bernd Kleinjohann. “Combining Automatic Service Composition with Adaptive Service Recommendation for Dynamic Markets of Services.” In <i>Proceedings of the 10th World Congress on Services (SERVICES)</i>, 346–53, 2014. <a href=\"https://doi.org/10.1109/SERVICES.2014.68\">https://doi.org/10.1109/SERVICES.2014.68</a>.","apa":"Jungmann, A., Mohr, F., &#38; Kleinjohann, B. (2014). Combining Automatic Service Composition with Adaptive Service Recommendation for Dynamic Markets of Services. In <i>Proceedings of the 10th World Congress on Services (SERVICES)</i> (pp. 346–353). <a href=\"https://doi.org/10.1109/SERVICES.2014.68\">https://doi.org/10.1109/SERVICES.2014.68</a>","short":"A. Jungmann, F. Mohr, B. Kleinjohann, in: Proceedings of the 10th World Congress on Services (SERVICES), 2014, pp. 346–353."},"year":"2014","status":"public","author":[{"first_name":"Alexander","last_name":"Jungmann","full_name":"Jungmann, Alexander"},{"full_name":"Mohr, Felix","last_name":"Mohr","first_name":"Felix"},{"last_name":"Kleinjohann","full_name":"Kleinjohann, Bernd","first_name":"Bernd"}],"doi":"10.1109/SERVICES.2014.68","page":"346-353","file":[{"file_id":"1347","file_name":"447-_FINAL__Combining_Automatic_Service_Composition_with_Adaptive_Service_Recommendation_for_Dynamic_Markets_of_Services.pdf","success":1,"date_updated":"2018-03-16T11:26:36Z","date_created":"2018-03-16T11:26:36Z","creator":"florida","file_size":429462,"content_type":"application/pdf","access_level":"closed","relation":"main_file"}],"ddc":["040"],"file_date_updated":"2018-03-16T11:26:36Z","date_created":"2017-10-17T12:42:19Z","project":[{"name":"SFB 901","_id":"1"},{"_id":"10","name":"SFB 901 - Subprojekt B2"},{"name":"SFB 901 - Project Area B","_id":"3"}],"has_accepted_license":"1","abstract":[{"lang":"eng","text":"Automatic service composition is still a challengingtask. It is even more challenging when dealing witha dynamic market of services for end users. New servicesmay enter the market while other services are completelyremoved. Furthermore, end users are typically no experts in thedomain in which they formulate a request. As a consequence,ambiguous user requests will inevitably emerge and have tobe taken into account. To meet these challenges, we proposea new approach that combines automatic service compositionwith adaptive service recommendation. A best first backwardsearch algorithm produces solutions that are functional correctwith respect to user requests. An adaptive recommendationsystem supports the search algorithm in decision-making.Reinforcement Learning techniques enable the system to adjustits recommendation strategy over time based on user ratings.The integrated approach is described on a conceptional leveland demonstrated by means of an illustrative example fromthe image processing domain."}]}