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Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.","mla":"Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 2017, pp. 1–12.","bibtex":"@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics}, booktitle={Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017}, author={Melnikov, Vitaly and Hüllermeier, Eyke}, year={2017}, pages={1–12} }","apa":"Melnikov, V., & Hüllermeier, E. (2017). Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics. In Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017 (pp. 1–12).","ama":"Melnikov V, Hüllermeier E. Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics. In: Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017. ; 2017:1-12.","chicago":"Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” In Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 1–12, 2017."},"year":"2017","type":"conference","date_updated":"2022-01-06T06:50:31Z","_id":"10213"},{"status":"public","date_created":"2019-06-07T16:00:10Z","author":[{"last_name":"Shaker","full_name":"Shaker, Ammar","first_name":"Ammar"},{"last_name":"Heldt","first_name":"W.","full_name":"Heldt, W."},{"first_name":"Eyke","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","id":"48129"}],"publication":"Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia","department":[{"_id":"34"},{"_id":"7"},{"_id":"355"}],"user_id":"49109","title":"Learning TSK Fuzzy Rules from Data Streams","language":[{"iso":"eng"}],"year":"2017","type":"conference","citation":{"chicago":"Shaker, Ammar, W. Heldt, and Eyke Hüllermeier. “Learning TSK Fuzzy Rules from Data Streams.” In Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.","apa":"Shaker, A., Heldt, W., & Hüllermeier, E. (2017). Learning TSK Fuzzy Rules from Data Streams. In Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia.","ama":"Shaker A, Heldt W, Hüllermeier E. Learning TSK Fuzzy Rules from Data Streams. In: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia. ; 2017.","mla":"Shaker, Ammar, et al. “Learning TSK Fuzzy Rules from Data Streams.” Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.","bibtex":"@inproceedings{Shaker_Heldt_Hüllermeier_2017, title={Learning TSK Fuzzy Rules from Data Streams}, booktitle={Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia}, author={Shaker, Ammar and Heldt, W. and Hüllermeier, Eyke}, year={2017} }","short":"A. Shaker, W. Heldt, E. Hüllermeier, in: Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.","ieee":"A. Shaker, W. Heldt, and E. Hüllermeier, “Learning TSK Fuzzy Rules from Data Streams,” in Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017."},"date_updated":"2022-01-06T06:50:32Z","_id":"10216"},{"date_updated":"2022-01-06T06:50:33Z","_id":"10267","intvolume":" 258","issue":"1","page":"295-306","type":"journal_article","citation":{"chicago":"Bräuning, M., Eyke Hüllermeier, T. Keller, and M. Glaum. “Lexicographic Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning Method with an Application in Accounting.” European Journal of Operational Research 258, no. 1 (2017): 295–306.","apa":"Bräuning, M., Hüllermeier, E., Keller, T., & Glaum, M. (2017). Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting. European Journal of Operational Research, 258(1), 295–306.","ama":"Bräuning M, Hüllermeier E, Keller T, Glaum M. Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting. European Journal of Operational Research. 2017;258(1):295-306.","mla":"Bräuning, M., et al. “Lexicographic Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning Method with an Application in Accounting.” European Journal of Operational Research, vol. 258, no. 1, 2017, pp. 295–306.","bibtex":"@article{Bräuning_Hüllermeier_Keller_Glaum_2017, title={Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting}, volume={258}, number={1}, journal={European Journal of Operational Research}, author={Bräuning, M. and Hüllermeier, Eyke and Keller, T. and Glaum, M.}, year={2017}, pages={295–306} }","short":"M. Bräuning, E. Hüllermeier, T. Keller, M. Glaum, European Journal of Operational Research 258 (2017) 295–306.","ieee":"M. Bräuning, E. Hüllermeier, T. Keller, and M. Glaum, “Lexicographic preferences for predictive modeling of human decision making. A new machine learning method with an application in accounting,” European Journal of Operational Research, vol. 258, no. 1, pp. 295–306, 2017."},"year":"2017","language":[{"iso":"eng"}],"title":"Lexicographic preferences for predictive modeling of human decision making. 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Schäfer. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering 43, no. 8 (2017): 739–59.","bibtex":"@article{Platenius_Shaker_Becker_Hüllermeier_Schäfer_2017, title={Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic}, volume={43}, number={8}, journal={IEEE Transactions on Software Engineering}, author={Platenius, M.-C. and Shaker, Ammar and Becker, M. and Hüllermeier, Eyke and Schäfer, W.}, year={2017}, pages={739–759} }","mla":"Platenius, M. C., et al. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering, vol. 43, no. 8, 2017, pp. 739–59.","short":"M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions on Software Engineering 43 (2017) 739–759.","ieee":"M.-C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, and W. Schäfer, “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic,” IEEE Transactions on Software Engineering, vol. 43, no. 8, pp. 739–759, 2017."},"type":"journal_article","year":"2017","page":"739-759"},{"status":"public","date_created":"2019-06-18T15:53:28Z","author":[{"first_name":"Eyke","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","id":"48129"}],"publication":"The Computing Research Repository (CoRR)","department":[{"_id":"34"},{"_id":"7"},{"_id":"355"}],"user_id":"49109","title":"From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection","language":[{"iso":"eng"}],"citation":{"ieee":"E. Hüllermeier, “From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection,” The Computing Research Repository (CoRR), 2017.","short":"E. Hüllermeier, The Computing Research Repository (CoRR) (2017).","bibtex":"@article{Hüllermeier_2017, title={From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection}, number={abs/1712.00646}, journal={The Computing Research Repository (CoRR)}, author={Hüllermeier, Eyke}, year={2017} }","mla":"Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy Rule-Based Systems: A Critical Reflection.” The Computing Research Repository (CoRR), abs/1712.00646, 2017.","chicago":"Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy Rule-Based Systems: A Critical Reflection.” The Computing Research Repository (CoRR), 2017.","ama":"Hüllermeier E. From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection. The Computing Research Repository (CoRR). 2017.","apa":"Hüllermeier, E. (2017). From Knowledge-based to Data-driven Modeling of Fuzzy Rule-based Systems: A Critical Reflection. The Computing Research Repository (CoRR)."},"type":"journal_article","year":"2017","article_number":"abs/1712.00646 ","date_updated":"2022-01-06T06:50:33Z","_id":"10269"},{"status":"public","date_created":"2021-09-10T10:21:49Z","volume":88,"author":[{"id":"66937","last_name":"Ramaswamy","full_name":"Ramaswamy, Arunselvan","orcid":"https://orcid.org/ 0000-0001-7547-8111","first_name":"Arunselvan"},{"full_name":"Bhatnagar, Shalabh","first_name":"Shalabh","last_name":"Bhatnagar"}],"publisher":"Taylor \\& Francis","publication":"Stochastics","department":[{"_id":"355"}],"user_id":"66937","title":"Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem","extern":"1","language":[{"iso":"eng"}],"year":"2016","type":"journal_article","citation":{"ieee":"A. Ramaswamy and S. Bhatnagar, “Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem,” Stochastics, vol. 88, no. 8, pp. 1173–1187, 2016.","short":"A. Ramaswamy, S. Bhatnagar, Stochastics 88 (2016) 1173–1187.","mla":"Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics, vol. 88, no. 8, Taylor \\& Francis, 2016, pp. 1173–87.","bibtex":"@article{Ramaswamy_Bhatnagar_2016, title={Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem}, volume={88}, number={8}, journal={Stochastics}, publisher={Taylor \\& Francis}, author={Ramaswamy, Arunselvan and Bhatnagar, Shalabh}, year={2016}, pages={1173–1187} }","chicago":"Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics 88, no. 8 (2016): 1173–87.","ama":"Ramaswamy A, Bhatnagar S. Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem. Stochastics. 2016;88(8):1173-1187.","apa":"Ramaswamy, A., & Bhatnagar, S. (2016). Stochastic recursive inclusion in two timescales with an application to the lagrangian dual problem. Stochastics, 88(8), 1173–1187."},"page":"1173-1187","issue":"8","date_updated":"2022-01-06T06:56:08Z","_id":"24154","intvolume":" 88"},{"language":[{"iso":"eng"}],"doi":"10.4467/20838476si.16.006.6187","date_updated":"2022-01-06T06:59:10Z","project":[{"name":"SFB 901 - Project Area B","_id":"3"},{"name":"SFB 901 - Subproject B3","_id":"11"},{"name":"SFB 901 - Subproject A4","_id":"8"},{"name":"SFB 901","_id":"1"},{"_id":"2","name":"SFB 901 - Project Area A"}],"publication_status":"published","publication_identifier":{"issn":["2083-8476"]},"department":[{"_id":"355"},{"_id":"183"}],"title":"Pairwise versus Pointwise Ranking: A Case Study","year":"2016","citation":{"ieee":"V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, and Pritha Gupta, “Pairwise versus Pointwise Ranking: A Case Study,” Schedae Informaticae, vol. 25, 2016.","short":"V. Melnikov, E. Hüllermeier, D. Kaimann, B. Frick, Pritha Gupta, Schedae Informaticae 25 (2016).","bibtex":"@article{Melnikov_Hüllermeier_Kaimann_Frick_Gupta_2016, title={Pairwise versus Pointwise Ranking: A Case Study}, volume={25}, DOI={10.4467/20838476si.16.006.6187}, journal={Schedae Informaticae}, publisher={Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego}, author={Melnikov, Vitalik and Hüllermeier, Eyke and Kaimann, Daniel and Frick, Bernd and Gupta, Pritha }, year={2016} }","mla":"Melnikov, Vitalik, et al. “Pairwise versus Pointwise Ranking: A Case Study.” Schedae Informaticae, vol. 25, Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego, 2016, doi:10.4467/20838476si.16.006.6187.","ama":"Melnikov V, Hüllermeier E, Kaimann D, Frick B, Gupta Pritha . Pairwise versus Pointwise Ranking: A Case Study. Schedae Informaticae. 2016;25. doi:10.4467/20838476si.16.006.6187","apa":"Melnikov, V., Hüllermeier, E., Kaimann, D., Frick, B., & Gupta, Pritha . (2016). Pairwise versus Pointwise Ranking: A Case Study. Schedae Informaticae, 25. https://doi.org/10.4467/20838476si.16.006.6187","chicago":"Melnikov, Vitalik, Eyke Hüllermeier, Daniel Kaimann, Bernd Frick, and Pritha Gupta. “Pairwise versus Pointwise Ranking: A Case Study.” Schedae Informaticae 25 (2016). https://doi.org/10.4467/20838476si.16.006.6187."},"type":"journal_article","intvolume":" 25","_id":"3318","has_accepted_license":"1","status":"public","date_created":"2018-06-22T14:49:40Z","volume":25,"file":[{"file_name":"roz-6-Melnikov.pdf","date_created":"2018-11-02T15:54:38Z","access_level":"closed","file_id":"5317","creator":"ups","file_size":1002478,"relation":"main_file","success":1,"content_type":"application/pdf","date_updated":"2018-11-02T15:54:38Z"}],"author":[{"first_name":"Vitalik","full_name":"Melnikov, Vitalik","last_name":"Melnikov"},{"full_name":"Hüllermeier, Eyke","first_name":"Eyke","id":"48129","last_name":"Hüllermeier"},{"id":"18949","last_name":"Kaimann","full_name":"Kaimann, Daniel","first_name":"Daniel"},{"full_name":"Frick, Bernd ","first_name":"Bernd ","last_name":"Frick"},{"full_name":"Gupta, Pritha ","first_name":" Pritha ","last_name":"Gupta"}],"publisher":"Uniwersytet Jagiellonski - Wydawnictwo Uniwersytetu Jagiellonskiego","publication":"Schedae Informaticae","file_date_updated":"2018-11-02T15:54:38Z","user_id":"15504","ddc":["000"]},{"year":"2016","type":"journal_article","citation":{"chicago":"Platenius, Marie Christin, Ammar Shaker, Matthias Becker, Eyke Hüllermeier, and Wilhelm Schäfer. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, no. 8 (2016): 739–59. https://doi.org/10.1109/TSE.2016.2632115.","apa":"Platenius, M. C., Shaker, A., Becker, M., Hüllermeier, E., & Schäfer, W. (2016). Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic. IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, (8), 739–759. https://doi.org/10.1109/TSE.2016.2632115","ama":"Platenius MC, Shaker A, Becker M, Hüllermeier E, Schäfer W. Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic. IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017. 2016;(8):739-759. doi:10.1109/TSE.2016.2632115","bibtex":"@article{Platenius_Shaker_Becker_Hüllermeier_Schäfer_2016, title={Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic}, DOI={10.1109/TSE.2016.2632115}, number={8}, journal={IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017}, publisher={IEEE}, author={Platenius, Marie Christin and Shaker, Ammar and Becker, Matthias and Hüllermeier, Eyke and Schäfer, Wilhelm}, year={2016}, pages={739–759} }","mla":"Platenius, Marie Christin, et al. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, no. 8, IEEE, 2016, pp. 739–59, doi:10.1109/TSE.2016.2632115.","short":"M.C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, W. Schäfer, IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017 (2016) 739–759.","ieee":"M. C. Platenius, A. Shaker, M. Becker, E. Hüllermeier, and W. Schäfer, “Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic,” IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017, no. 8, pp. 739–759, 2016."},"page":"739-759","_id":"190","issue":"8","publisher":"IEEE","author":[{"full_name":"Platenius, Marie Christin","first_name":"Marie Christin","last_name":"Platenius"},{"full_name":"Shaker, Ammar","first_name":"Ammar","last_name":"Shaker"},{"first_name":"Matthias","full_name":"Becker, Matthias","last_name":"Becker"},{"id":"48129","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","first_name":"Eyke"},{"first_name":"Wilhelm","full_name":"Schäfer, Wilhelm","last_name":"Schäfer"}],"file_date_updated":"2018-03-21T12:30:31Z","publication":"IEEE Transactions on Software Engineering (TSE), presented at ICSE 2017","file":[{"success":1,"relation":"main_file","content_type":"application/pdf","date_updated":"2018-03-21T12:30:31Z","file_id":"1529","creator":"florida","file_size":5225413,"access_level":"closed","date_created":"2018-03-21T12:30:31Z","file_name":"190-07755807.pdf"}],"status":"public","has_accepted_license":"1","date_created":"2017-10-17T12:41:29Z","abstract":[{"lang":"eng","text":"Today, software components are provided by global markets in the form of services. In order to optimally satisfy service requesters and service providers, adequate techniques for automatic service matching are needed. However, a requester’s requirements may be vague and the information available about a provided service may be incomplete. As a consequence, fuzziness is induced into the matching procedure. The contribution of this paper is the development of a systematic matching procedure that leverages concepts and techniques from fuzzy logic and possibility theory based on our formal distinction between different sources and types of fuzziness in the context of service matching. In contrast to existing methods, our approach is able to deal with imprecision and incompleteness in service specifications and to inform users about the extent of induced fuzziness in order to improve the user’s decision-making. We demonstrate our approach on the example of specifications for service reputation based on ratings given by previous users. Our evaluation based on real service ratings shows the utility and applicability of our approach."}],"ddc":["040"],"user_id":"15504","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:53:57Z","doi":"10.1109/TSE.2016.2632115","department":[{"_id":"355"}],"project":[{"_id":"1","name":"SFB 901"},{"_id":"9","name":"SFB 901 - Subprojekt B1"},{"_id":"10","name":"SFB 901 - Subprojekt B2"},{"_id":"11","name":"SFB 901 - Subprojekt B3"},{"name":"SFB 901 - Project Area B","_id":"3"}],"title":"Imprecise Matching of Requirements Specifications for Software Services using Fuzzy Logic"},{"_id":"184","type":"conference","year":"2016","citation":{"ama":"Melnikov V, Hüllermeier E. Learning to Aggregate Using Uninorms. In: Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016). LNCS. ; 2016:756-771. doi:10.1007/978-3-319-46227-1_47","apa":"Melnikov, V., & Hüllermeier, E. (2016). Learning to Aggregate Using Uninorms. In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016) (pp. 756–771). https://doi.org/10.1007/978-3-319-46227-1_47","chicago":"Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.” In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 756–71. LNCS, 2016. https://doi.org/10.1007/978-3-319-46227-1_47.","bibtex":"@inproceedings{Melnikov_Hüllermeier_2016, series={LNCS}, title={Learning to Aggregate Using Uninorms}, DOI={10.1007/978-3-319-46227-1_47}, booktitle={Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016)}, author={Melnikov, Vitaly and Hüllermeier, Eyke}, year={2016}, pages={756–771}, collection={LNCS} }","mla":"Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.” Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–71, doi:10.1007/978-3-319-46227-1_47.","short":"V. Melnikov, E. Hüllermeier, in: Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–771.","ieee":"V. Melnikov and E. Hüllermeier, “Learning to Aggregate Using Uninorms,” in Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 2016, pp. 756–771."},"page":"756-771","user_id":"15504","ddc":["040"],"abstract":[{"text":"In this paper, we propose a framework for a class of learning problems that we refer to as “learning to aggregate”. Roughly, learning-to-aggregate problems are supervised machine learning problems, in which instances are represented in the form of a composition of a (variable) number on constituents; such compositions are associated with an evaluation, score, or label, which is the target of the prediction task, and which can presumably be modeled in the form of a suitable aggregation of the properties of its constituents. Our learning-to-aggregate framework establishes a close connection between machine learning and a branch of mathematics devoted to the systematic study of aggregation functions. We specifically focus on a class of functions called uninorms, which combine conjunctive and disjunctive modes of aggregation. Experimental results for a corresponding model are presented for a review data set, for which the aggregation problem consists of combining different reviewer opinions about a paper into an overall decision of acceptance or rejection.","lang":"eng"}],"has_accepted_license":"1","status":"public","date_created":"2017-10-17T12:41:27Z","file":[{"creator":"florida","file_id":"1533","file_size":472159,"relation":"main_file","success":1,"date_updated":"2018-03-21T12:32:44Z","content_type":"application/pdf","file_name":"184-chp_3A10.1007_2F978-3-319-46227-1_47.pdf","date_created":"2018-03-21T12:32:44Z","access_level":"closed"}],"author":[{"last_name":"Melnikov","id":"58747","first_name":"Vitaly","full_name":"Melnikov, Vitaly"},{"first_name":"Eyke","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","id":"48129"}],"file_date_updated":"2018-03-21T12:32:44Z","publication":"Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016)","doi":"10.1007/978-3-319-46227-1_47","date_updated":"2022-01-06T06:53:32Z","language":[{"iso":"eng"}],"series_title":"LNCS","title":"Learning to Aggregate Using Uninorms","project":[{"_id":"1","name":"SFB 901"},{"_id":"11","name":"SFB 901 - Subprojekt B3"},{"name":"SFB 901 - Project Area B","_id":"3"}],"department":[{"_id":"355"}]},{"publisher":"Springer","author":[{"first_name":"J.","full_name":"Fürnkranz, J.","last_name":"Fürnkranz"},{"id":"48129","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","first_name":"Eyke"}],"publication":"Encyclopedia of Machine Learning and Data Mining","department":[{"_id":"34"},{"_id":"7"},{"_id":"355"}],"status":"public","date_created":"2019-07-10T16:00:23Z","editor":[{"first_name":"C.","full_name":"Sammut, C.","last_name":"Sammut"},{"first_name":"G.I.","full_name":"Webb, G.I.","last_name":"Webb"}],"user_id":"49109","title":"Preference Learning","language":[{"iso":"eng"}],"year":"2016","type":"encyclopedia_article","citation":{"chicago":"Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia of Machine Learning and Data Mining, edited by C. 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Pfannschmidt (Eds.), Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning."},"user_id":"49109","title":"Preference-Based Reinforcement Learning Using Dyad Ranking","department":[{"_id":"34"},{"_id":"7"},{"_id":"355"}],"publication":"Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning","author":[{"last_name":"Schäfer","first_name":"Dirk","full_name":"Schäfer, Dirk"},{"full_name":"Hüllermeier, Eyke","first_name":"Eyke","id":"48129","last_name":"Hüllermeier"}],"date_created":"2019-06-11T15:37:51Z","status":"public","editor":[{"last_name":"Busa-Fekete","full_name":"Busa-Fekete, Robert","first_name":"Robert"},{"last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","first_name":"Eyke"},{"first_name":"V.","full_name":"Mousseau, V.","last_name":"Mousseau"},{"last_name":"Pfannschmidt","full_name":"Pfannschmidt, Karlson","first_name":"Karlson"}]},{"title":"Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators","user_id":"49109","department":[{"_id":"34"},{"_id":"7"},{"_id":"355"}],"publication":"Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning","author":[{"last_name":"Couso","full_name":"Couso, Ines","first_name":"Ines"},{"full_name":"Ahmadi Fahandar, Mohsen","first_name":"Mohsen","last_name":"Ahmadi Fahandar"},{"full_name":"Hüllermeier, Eyke","first_name":"Eyke","id":"48129","last_name":"Hüllermeier"}],"editor":[{"last_name":"Busa-Fekete","first_name":"Robert","full_name":"Busa-Fekete, Robert"},{"last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","first_name":"Eyke"},{"last_name":"Mousseau","first_name":"V.","full_name":"Mousseau, V."},{"last_name":"Pfannschmidt","first_name":"Karlson","full_name":"Pfannschmidt, Karlson"}],"date_created":"2019-06-11T15:41:55Z","status":"public","_id":"10229","date_updated":"2022-01-06T06:50:32Z","year":"2016","type":"conference","citation":{"short":"I. 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Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators. In: Busa-Fekete R, Hüllermeier E, Mousseau V, Pfannschmidt K, eds. Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning. ; 2016.","chicago":"Couso, Ines, Mohsen Ahmadi Fahandar, and Eyke Hüllermeier. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” In Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete, Eyke Hüllermeier, V. Mousseau, and Karlson Pfannschmidt, 2016.","bibtex":"@inproceedings{Couso_Ahmadi Fahandar_Hüllermeier_2016, title={Statistical Inference for Incomplete Ranking Data: A Comparison of two likelihood-based estimators}, booktitle={Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning}, author={Couso, Ines and Ahmadi Fahandar, Mohsen and Hüllermeier, Eyke}, editor={Busa-Fekete, Robert and Hüllermeier, Eyke and Mousseau, V. and Pfannschmidt, KarlsonEditors}, year={2016} }","mla":"Couso, Ines, et al. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” Proceedings DA2PL ´2016, Euro Mini Conference from Multiple Criteria Decision Aid to Preference Learning, edited by Robert Busa-Fekete et al., 2016."},"language":[{"iso":"eng"}]},{"_id":"10230","date_updated":"2022-01-06T06:50:32Z","language":[{"iso":"eng"}],"citation":{"ama":"Lu S, Hüllermeier E. 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The Hague, The Netherlands: IOS Press.","ama":"Kaminka GA, Fox M, Bouquet P, et al., eds. ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence. Vol 285. The Hague, The Netherlands: IOS Press; 2016.","chicago":"Kaminka, G.A., M. Fox, P. Bouquet, Eyke Hüllermeier, V. Dignum, F. Dignum, and F. van Harmelen, eds. ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence. Vol. 285. Frontiers in Artificial Intelligence and Applications, The Hague, The Netherlands. The Hague, The Netherlands: IOS Press, 2016.","ieee":"G. A. Kaminka et al., Eds., ECAI 2016, 22nd European Conference on Artificial Intelligence, including PAIS 2016, Prestigious Applications of Artificial Intelligence, vol. 285. The Hague, The Netherlands: IOS Press, 2016.","short":"G.A. Kaminka, M. Fox, P. Bouquet, E. Hüllermeier, V. Dignum, F. Dignum, F. van Harmelen, eds., ECAI 2016, 22nd European Conference on Artificial Intelligence, Including PAIS 2016, Prestigious Applications of Artificial Intelligence, IOS Press, The Hague, The Netherlands, 2016."},"type":"conference_editor","_id":"10263","date_updated":"2022-01-06T06:50:33Z","intvolume":" 285"},{"date_updated":"2022-01-06T06:50:33Z","_id":"10264","intvolume":" 28","issue":"6","language":[{"iso":"eng"}],"year":"2016","citation":{"ieee":"M. Leinweber et al., “CavSimBase: A database for large scale comparison of protein binding sites,” IEEE Transactions on Knowledge and Data Engineering, vol. 28, no. 6, pp. 1423–1434, 2016.","short":"M. Leinweber, T. Fober, M. Strickert, L. Baumgärtner, G. Klebe, B. Freisleben, E. 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In: Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet. ; 2015:333--340. doi:10.1109/SERVICES.2015.58","apa":"Arifulina, S., Platenius, M. C., Mohr, F., Engels, G., & Schäfer, W. (2015). Market-Specific Service Compositions: Specification and Matching. In Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet (pp. 333--340). https://doi.org/10.1109/SERVICES.2015.58","chicago":"Arifulina, Svetlana, Marie Christin Platenius, Felix Mohr, Gregor Engels, and Wilhelm Schäfer. “Market-Specific Service Compositions: Specification and Matching.” In Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet, 333--340, 2015. https://doi.org/10.1109/SERVICES.2015.58.","bibtex":"@inproceedings{Arifulina_Platenius_Mohr_Engels_Schäfer_2015, title={Market-Specific Service Compositions: Specification and Matching}, DOI={10.1109/SERVICES.2015.58}, booktitle={Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet}, author={Arifulina, Svetlana and Platenius, Marie Christin and Mohr, Felix and Engels, Gregor and Schäfer, Wilhelm}, year={2015}, pages={333--340} }","mla":"Arifulina, Svetlana, et al. “Market-Specific Service Compositions: Specification and Matching.” Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet, 2015, pp. 333--340, doi:10.1109/SERVICES.2015.58.","short":"S. Arifulina, M.C. Platenius, F. Mohr, G. Engels, W. Schäfer, in: Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet, 2015, pp. 333--340.","ieee":"S. Arifulina, M. C. Platenius, F. Mohr, G. Engels, and W. Schäfer, “Market-Specific Service Compositions: Specification and Matching,” in Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet, 2015, pp. 333--340."},"type":"conference","_id":"280","file":[{"creator":"florida","file_id":"1470","file_size":234260,"relation":"main_file","success":1,"content_type":"application/pdf","date_updated":"2018-03-21T09:26:04Z","file_name":"280-07196546.pdf","date_created":"2018-03-21T09:26:04Z","access_level":"closed"}],"publication":"Proceedings of the IEEE 11th World Congress on Services (SERVICES), Visionary Track: Service Composition for the Future Internet","file_date_updated":"2018-03-21T09:26:04Z","author":[{"last_name":"Arifulina","full_name":"Arifulina, Svetlana","first_name":"Svetlana"},{"full_name":"Platenius, Marie Christin","first_name":"Marie Christin","last_name":"Platenius"},{"last_name":"Mohr","first_name":"Felix","full_name":"Mohr, Felix"},{"full_name":"Engels, Gregor","first_name":"Gregor","id":"107","last_name":"Engels"},{"last_name":"Schäfer","first_name":"Wilhelm","full_name":"Schäfer, Wilhelm"}],"date_created":"2017-10-17T12:41:46Z","has_accepted_license":"1","status":"public","abstract":[{"text":"The Collaborative Research Centre \"On-The-Fly Computing\" works on foundations and principles for the vision of the Future Internet. It proposes the paradigm of On-The-Fly Computing, which tackles emerging worldwide service markets. In these markets, service providers trade software, platform, and infrastructure as a service. Service requesters state requirements on services. To satisfy these requirements, the new role of brokers, who are (human) actors building service compositions on the fly, is introduced. Brokers have to specify service compositions formally and comprehensively using a domain-specific language (DSL), and to use service matching for the discovery of the constituent services available in the market. The broker's choice of the DSL and matching approaches influences her success of building compositions as distinctive properties of different service markets play a significant role. In this paper, we propose a new approach of engineering a situation-specific DSL by customizing a comprehensive, modular DSL and its matching for given service market properties. This enables the broker to create market-specific composition specifications and to perform market-specific service matching. As a result, the broker builds service compositions satisfying the requester's requirements more accurately. We evaluated the presented concepts using case studies in service markets for tourism and university management.","lang":"eng"}],"user_id":"477","ddc":["040"],"language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:57:49Z","doi":"10.1109/SERVICES.2015.58","department":[{"_id":"66"},{"_id":"76"},{"_id":"355"}],"project":[{"name":"SFB 901","_id":"1"},{"name":"SFB 901 - Subprojekt B1","_id":"9"},{"_id":"10","name":"SFB 901 - Subproject B2"},{"_id":"3","name":"SFB 901 - Project Area B"}],"title":"Market-Specific Service Compositions: Specification and Matching"},{"abstract":[{"lang":"eng","text":"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."}],"ddc":["040"],"user_id":"477","publication":"Journal of Internet Services and Applications","file_date_updated":"2018-03-20T07:39:17Z","author":[{"full_name":"Jungmann, Alexander","first_name":"Alexander","last_name":"Jungmann"},{"last_name":"Mohr","full_name":"Mohr, Felix","first_name":"Felix"}],"publisher":"Springer","file":[{"access_level":"closed","date_created":"2018-03-20T07:39:17Z","file_name":"323-An_approach_towards_adaptive_service_composition_in_markets_of_composed_services.pdf","relation":"main_file","success":1,"content_type":"application/pdf","date_updated":"2018-03-20T07:39:17Z","file_id":"1429","creator":"florida","file_size":2842281}],"date_created":"2017-10-17T12:41:55Z","status":"public","has_accepted_license":"1","_id":"323","issue":"1","page":"1-18","citation":{"mla":"Jungmann, Alexander, and Felix Mohr. “An Approach towards Adaptive Service Composition in Markets of Composed Services.” Journal of Internet Services and Applications, no. 1, Springer, 2015, pp. 1–18, doi:10.1186/s13174-015-0022-8.","bibtex":"@article{Jungmann_Mohr_2015, title={An approach towards adaptive service composition in markets of composed services}, DOI={10.1186/s13174-015-0022-8}, number={1}, journal={Journal of Internet Services and Applications}, publisher={Springer}, author={Jungmann, Alexander and Mohr, Felix}, year={2015}, pages={1–18} }","apa":"Jungmann, A., & Mohr, F. 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One of the most important qualities is the functionalreusability, which indicates how relevant the task is that a service solves.Current metrics for functional reusability of software, however, have verylittle explanatory power and do not accomplish this goal.This paper presents a new approach to estimate the functional reusabilityof services based on their relevance. To this end, it denes the degreeto which a service enables the execution of other services as its contri-bution. Based on the contribution, relevance of services is dened as anestimation for their functional reusability. Explanatory power is obtainedby normalizing relevance values with a reference service. The applicationof the metric to a service test set conrms its supposed capabilities.","lang":"eng"}],"language":[{"iso":"eng"}],"series_title":"LNCS","doi":"10.1007/978-3-319-14130-5_21","date_updated":"2022-01-06T06:59:07Z","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Subprojekt B2","_id":"10"},{"name":"SFB 901 - Project Area B","_id":"3"}],"department":[{"_id":"355"}],"title":"A Metric for Functional Reusability of Services"},{"language":[{"iso":"eng"}],"doi":"10.1109/SCC.2015.18","date_updated":"2022-01-06T06:59:04Z","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Subprojekt B2","_id":"10"},{"_id":"3","name":"SFB 901 - Project Area B"}],"department":[{"_id":"355"}],"title":"Automated Online Service Composition","citation":{"chicago":"Mohr, Felix, Alexander Jungmann, and Hans Kleine Büning. “Automated Online Service Composition.” In Proceedings of the 12th IEEE International Conference on Services Computing (SCC), 57--64, 2015. https://doi.org/10.1109/SCC.2015.18.","ama":"Mohr F, Jungmann A, Kleine Büning H. 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Kleine Büning, in: Proceedings of the 12th IEEE International Conference on Services Computing (SCC), 2015, pp. 57--64.","ieee":"F. Mohr, A. Jungmann, and H. 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The automated composition of services to a target software artifact has been tackled with many AI techniques, but existing approaches make unreasonably strong assumptions such as a predefined data flow, are limited to tiny problem sizes, ignore non-functional properties, or assume offline service repositories. This paper presents an algorithm that automatically composes services without making such assumptions. We employ a backward search algorithm that starts from an empty composition and prepends service calls to already discovered candidates until a solution is found. Available services are determined during the search process. We implemented our algorithm, performed an experimental evaluation, and compared it to other approaches."}]},{"issue":"6","_id":"4792","intvolume":" 23","citation":{"short":"R. Senge, E. Hüllermeier, IEEE Transactions on Fuzzy Systems 23 (2015) 2024–2033.","ieee":"R. Senge and E. 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