TY - CONF AB - Automatically composing service-based software solutionsis still a challenging task. Functional as well as nonfunctionalproperties have to be considered in order to satisfyindividual user requests. Regarding non-functional properties,the composition process can be modeled as optimization problemand solved accordingly. Functional properties, in turn, can bedescribed by means of a formal specification language. Statespacebased planning approaches can then be applied to solvethe underlying composition problem. However, depending on theexpressiveness of the applied formalism and the completenessof the functional descriptions, formally equivalent services maystill differ with respect to their implemented functionality. As aconsequence, the most appropriate solution for a desired functionalitycan hardly be determined without considering additionalinformation. In this paper, we demonstrate how to overcome thislack of information by means of Reinforcement Learning. Inorder to resolve ambiguity, we expand state-space based servicecomposition by a recommendation mechanism that supportsdecision-making beyond formal specifications. The recommendationmechanism adjusts its recommendation strategy basedon feedback from previous composition runs. Image processingserves as case study. Experimental results show the benefit of ourproposed solution. AU - Jungmann, Alexander AU - Mohr, Felix AU - Kleinjohann, Bernd ID - 457 T2 - Proceedings of the 7th International Conference on Service Oriented Computing and Applications (SOCA) TI - Applying Reinforcement Learning for Resolving Ambiguity in Service Composition ER - TY - CONF AB - Services are self-contained software components that can be used platform independent and that aim at maximizing software reuse. A basic concern in service oriented architectures is to measure the reusability of services. One of the most important qualities is the functional reusability, which indicates how relevant the task is that a service solves. Current metrics for functional reusability of software, however, either require source code analysis or have very little explanatory power. This paper gives a formally described vision statement for the estimation of functional reusability of services and sketches an exemplary reusability metric that is based on the service descriptions. AU - Mohr, Felix ID - 428 T2 - Proceedings of the 12th International Conference on Service Oriented Computing (ICSOC) TI - Estimating Functional Reusability of Services ER - TY - JOUR AU - Agarwal, M. AU - Fallah Tehrani, A. AU - Hüllermeier, Eyke ID - 16046 IS - 3-4 JF - Journal of Multi-Criteria Decision Analysis TI - Preference-based learning of ideal solutions in TOPSIS-like decision models VL - 22 ER - TY - JOUR AU - Krotzky, T. AU - Fober, T. AU - Hüllermeier, Eyke AU - Klebe, G. ID - 16060 IS - 5 JF - IEEE/ACM Transactions of Computational Biology and Bioinformatics TI - Extended graph-based models for enhanced similarity search in Cabase VL - 11 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 16064 IS - 7 JF - International Journal of Approximate Reasoning TI - Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization VL - 55 ER - TY - JOUR AU - Henzgen, Sascha AU - Strickert, M. AU - Hüllermeier, Eyke ID - 16069 JF - Evolving Systems TI - Visualization of evolving fuzzy-rule-based systems VL - 5 ER - TY - JOUR AU - Busa-Fekete, Robert AU - Szörenyi, B. AU - Weng, P. AU - Cheng, W. AU - Hüllermeier, Eyke ID - 16077 IS - 3 JF - Machine Learning TI - Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm. VL - 97 ER - TY - JOUR AU - Krempl, G. AU - Zliobaite, I. AU - Brzezinski, D. AU - Hüllermeier, Eyke AU - Last, M. AU - Lemaire, V. AU - Noack, T. AU - Shaker, A. AU - Sievi, S. AU - Spiliopoulou, M. AU - Stefanowski, J. ID - 16078 IS - 1 JF - SIGKDD Explorations TI - Open challenges for data stream mining research VL - 16 ER - TY - JOUR AU - Strickert, M. AU - Bunte, K. AU - Schleif, F.M. AU - Hüllermeier, Eyke ID - 16079 JF - Neurocomputing TI - Correlation-based embedding of pairwise score data VL - 141 ER - TY - JOUR AU - Shaker, Ammar AU - Hüllermeier, Eyke ID - 16080 IS - 1 JF - International Journal of Applied Mathematics and Computer Science TI - Survival analysis on data streams: Analyzing temporal events in dynamically changing environments VL - 24 ER - TY - JOUR AU - Senge, Robin AU - Bösner, S. AU - Dembczynski, K. AU - Haasenritter, J. AU - Hirsch, O. AU - Donner-Banzhoff, N. AU - Hüllermeier, Eyke ID - 16082 JF - Information Sciences TI - Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty VL - 255 ER - TY - JOUR AU - Donner-Banzhoff, N. AU - Haasenritter, J. AU - Hüllermeier, Eyke AU - Viniol, A. AU - Bösner, S. AU - Becker, A. ID - 16083 IS - 67 JF - Journal of Clinical Epidemiology TI - The comprehensive diagnostic study is suggested as a design to model the diagnostic process VL - 2 ER - TY - CONF AU - Busa-Fekete, Robert AU - Szörényi, B. AU - Hüllermeier, Eyke ID - 10247 T2 - Proceedings AAAI 2014, Quebec, Canada TI - PAC Rank Elicitation through Adaptive Sampling of Stochastic Pairwise Preferences ER - TY - CONF AU - Busa-Fekete, Robert AU - Hüllermeier, Eyke ID - 10248 T2 - Proceedings Int. Conf. on Algorithmic Learning Theory (ALT), Bled, Slovenia TI - A Survey of Preference-Based Online Learning with Bandit Algorithms ER - TY - CONF AU - Henzgen, Sascha AU - Hüllermeier, Eyke ID - 10249 T2 - Proceedings Discovery Science, Bled,Slovenia TI - Mining Rank Data ER - TY - CONF AU - Fallah Tehrani, A. AU - Strickert, M. AU - Hüllermeier, Eyke ID - 10250 T2 - Proceedings ESANN , Bruges, Belgium TI - The Choquet kernel for monotone data ER - TY - CONF AU - Abdel-Aziz, A. AU - Strickert, M. AU - Hüllermeier, Eyke ID - 10251 T2 - Proceedings Int. Conf. Case-Based Reasoning (ICCBR), Cork, Ireland TI - Learning Solution Similarity in Preference-Based CBR ER - TY - CONF AU - Schäfer, Dirk AU - Hüllermeier, Eyke ID - 10253 T2 - Proceedings Lernen-Wissensentdeckung-Adaptivität (LWA), Aachen, Germany TI - Dyad Ranking Using A Bilinear Plackett-Luce Model ER - TY - CONF AU - Calders, T. AU - Esposito, F. AU - Hüllermeier, Eyke AU - Meo, R. ID - 10254 T2 - Proceedings, Parts I-III. Lecture Notes in Computer Science TI - Machine Learning and Knowledge Discovery in Databases-European Conf. ECML/PKDD, Nancy, France ER - TY - CONF AU - Fürnkranz, J. AU - Hüllermeier, Eyke AU - Rudin, Cynthia AU - Slowinski, Roman AU - Sanner, Scott ID - 10295 IS - 3 TI - Preference Learning (Dagstuhl Seminar 14101) Dagstuhl Reports VL - 4 ER - TY - JOUR AU - Shaker, Ammar AU - Hüllermeier, Eyke ID - 10296 IS - 1 JF - Applied Mathematics and Computer Science TI - Survival analysis on data streams: Analyzing temporal events in dynamically changing environments VL - 24 ER - TY - JOUR AU - Hoffmann, F. AU - Hüllermeier, Eyke AU - Kroll, A. ID - 10297 IS - 10 JF - Computational Intelligence Automatisierungstechnik TI - Ausgewählte Beiträge des GMA-Fachausschusses 5.14 VL - 62 ER - TY - JOUR AU - Calders, T. AU - Esposito, F. AU - Hüllermeier, Eyke AU - Meo, R. ID - 10298 IS - 5-6 JF - Data Min. Knowledge Discovery TI - Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track VL - 28 ER - TY - JOUR AU - Henzgen, Sascha AU - Strickert, M. AU - Hüllermeier, Eyke ID - 10299 IS - 3 JF - Evolving Systems TI - Visualization of evolving fuzzy rule-based systems VL - 5 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 10308 IS - 7 JF - Int. J. Approx. Reasoning TI - Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization VL - 55 ER - TY - JOUR AU - Hüllermeier, Eyke ID - 10309 IS - 7 JF - Int. J. Approx. Reasoning TI - Rejoinder on "Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization VL - 55 ER - TY - JOUR AU - Strickert, M. AU - Bunte, K. AU - Schleif, F.- M. AU - Hüllermeier, Eyke ID - 10310 JF - Neurocomputing TI - Correlation-based embedding of pairwise score data VL - 141 ER - TY - JOUR AU - Senge, Robin AU - Bösner, S. AU - Dembczynski, K. AU - Haasenritter, J. AU - Hirsch, O. AU - Donner-Banzhoff, N. AU - Hüllermeier, Eyke ID - 10311 JF - Information Sciences TI - Reliable classification: Learning classifiers that distinguish aleatoric and epistemic uncertainty VL - 255 ER - TY - JOUR AU - Mernberger, M. AU - Moog, M. AU - Stork, S. AU - Zauner, S. AU - Maier, U.G. AU - Hüllermeier, Eyke ID - 10312 IS - 1 JF - J. Bioinformatics and Computational Biology TI - Protein Sub-Cellular Localization Prediction for Special compartments via Optimized Time Series Distances VL - 12 ER - TY - JOUR AU - Calders, T. AU - Esposito, F. AU - Hüllermeier, Eyke AU - Meo, R. ID - 10313 IS - 1-2 JF - Machine Learning TI - Guest editors`introduction:special issue of the ECML/PKDD 2014 journal track VL - 97 ER - TY - JOUR AU - Busa-Fekete, Robert AU - Szörényi, B. AU - Weng, P. AU - Cheng, W. AU - Hüllermeier, Eyke ID - 10314 IS - 3 JF - Machine Learning TI - Preference-Based Reinforcement Learning: evolutionary direct policy search using a preference-based racing algorithm VL - 97 ER - TY - JOUR AU - Montanés, E. AU - Senge, Robin AU - Barranquero, J. AU - Quevedo, J.R. AU - Del Coz, J.J. AU - Hüllermeier, Eyke ID - 10315 IS - 3 JF - Pattern Recognition TI - Dependent binary relevance models for multi-label classification VL - 47 ER - TY - JOUR AU - Krempl, G. AU - Zliobaite, I. AU - Brzezinski, D. AU - Hüllermeier, Eyke AU - Last, M. AU - Lemaire, V. AU - Noack, T. AU - Shaker, Ammar AU - Sievi, S. AU - Spiliopoulou, M. AU - Stefanowski, J. ID - 10316 IS - 1 JF - SIGKDD Explorations TI - Open challenges for data stream mining research VL - 16 ER - TY - JOUR AU - Krotzky, T. AU - Fober, T. AU - Hüllermeier, Eyke AU - Klebe, G. ID - 10317 IS - 5 JF - IEEE/ACM Trans. Comput. Biology Bioinform. TI - Extended Graph-Based Models for Enhanced Similarity Search in Cavbase VL - 11 ER - TY - JOUR AU - Stock, M. AU - Fober, T. AU - Hüllermeier, Eyke AU - Glinca, S, AU - Klebe, G. AU - Pahikkala, T. AU - Airola, A. AU - De Baets, B. AU - Wageman, W. ID - 10318 IS - 6 JF - IEEE/ACM Trans. Comput. Biology Bioinform. TI - Identification of Functionally Releated Enzymes by Learning to Rank Methods VL - 11 ER - TY - CONF AB - Software composition has been studied as a subject of state based planning for decades. Existing composition approaches that are efficient enough to be used in practice are limited to sequential arrangements of software components. This restriction dramatically reduces the number of composition problems that can be solved. However, there are many composition problems that could be solved by existing approaches if they had a possibility to combine components in very simple non-sequential ways. To this end, we present an approach that arranges not only basic components but also composite components. Composite components enhance the structure of the composition by conditional control flows. Through algorithms that are written by experts, composite components are automatically generated before the composition process starts. Therefore, our approach is not a substitute for existing composition algorithms but complements them with a preprocessing step. We verified the validity of our approach through implementation of the presented algorithms. AU - Mohr, Felix AU - Kleine Büning, Hans ID - 485 T2 - Proceedings of the 15th International Conference on Information Integration and Web-based Applications & Services (iiWAS) TI - Semi-Automated Software Composition Through Generated Components ER - TY - CONF AB - Automated service composition has been studied as a subject of state based planning for a decade. A great deal of service composition tasks can only be solved if concrete output values of the services are considered in the composition process. However, the fact that those values are not known before runtime leads to nondeterministic planning problems, which have proven to be notoriously difficult in practical automated service composition applications. Even though this problem is frequently recognized, it has still received remarkably few attention and remains unsolved.This paper shows how nondeterminism in automated service composition can be reduced. We introduce context rules as a means to derive semantic knowledge from output values of services. These rules enable us to replace nondeterministic composition operations by less nondeterministic or even completely deterministic ones. We show the validity of our solutions not only theoretically but also have evaluated them practically through implementation. AU - Mohr, Felix AU - Lettmann, Theodor AU - Kleine Büning, Hans ID - 495 T2 - Proceedings of the 6th International Conference on Service Oriented Computing and Applications (SOCA) TI - Reducing Nondeterminism in Automated Service Composition ER - TY - CONF AU - Cheng, W. AU - Henzgen, S. AU - Hüllermeier, Eyke ID - 15752 T2 - In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Bamberg, Germany TI - Labelwise versus pairwise decomposition in label ranking ER - TY - CONF AU - Senge, Robin AU - del Coz, J. AU - Hüllermeier, Eyke ID - 15753 T2 - In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Bamberg, Germany TI - Rectifying classifier chains for multi-label classification, Bamberg, Germany ER - TY - CONF AU - Busa-Fekete, Robert AU - Fober, T. AU - Hüllermeier, Eyke ED - Hoffmann, F. ED - Hüllermeier, Eyke ID - 15755 T2 - in Proceedings 23th Workshop Computational Intelligence, Dortmund Germany TI - Preference-based evolutionary optimization using generalized racing algorithms ER - TY - CONF AU - Henzgen, S. AU - Hüllermeier, Eyke ED - Hoffmann, F. ED - Hüllermeier, Eyke ID - 15756 T2 - in Proceedings 23th Workshop Computational Intelligence, Dortmund Germany TI - Weighted rank correlation measures based on fuzzy order relations ER - TY - CONF AU - Weng, P. AU - Busa-Fekete, Robert AU - Hüllermeier, Eyke ID - 15757 T2 - In Proceedings ECML/PKDD-Workshop on Reinforcement learning from Generalized Feedback:Beyond Numerical Rewards, Prague TI - Interactive Q-learning with ordinal rewards and unreliable tutor ER - TY - CONF AU - Busa-Fekete, Robert AU - Szörenyi, B. AU - Weng, P. AU - Hüllermeier, Eyke ID - 15758 T2 - In Proceedings ECML/PKDD-Workshop on Reinforcement learning from Generalized Feedback:Beyond Numerical Rewards, Prague TI - Preference-based evolutionary direct policy search ER - TY - CONF AU - Cheng, W. AU - Hüllermeier, Eyke ID - 15759 T2 - In Proceedings M-PREF`13, 7th Multidisciplinary Workshop on Advances in Preference Handling Beijing, China TI - A nearest neigbor approach to label ranking based on generalized labelwise loss minimization ER - TY - CONF AU - Shaker, Ammar AU - Hüllermeier, Eyke ED - Krempl, G. ED - Zliobaite, I. ED - Wang, Y. ED - Forman, G. ID - 15760 T2 - In Proceedings RealStream 2013, 1st International Workshop on Real-World Challenges for Data Stream Mining, Prague, Czech Republic TI - Event history analysis on data streams: An application to earthquake occurence ER - TY - CONF AU - Senge, Robin AU - del Coz, J.J. AU - Hüllermeier, Eyke ED - Schmidt-Thieme, L. ED - Spiliopoulou, M. ID - 15761 T2 - In Proceedings of GFKL-2012, 36th Annual Conference of the German Classification Society, Studies in Classification, Data Analysis and Knowledge Organization, Hildesheim, Germany TI - On the problem of error propagation in classier chains for multi-label classification. Data Analysis, Machine Learning and Knowledge Discovery ER - TY - CONF AU - Fober, T. AU - Klebe, G. AU - Hüllermeier, Eyke ED - Lausen, B. ED - Van den Poel, D. ED - Ultsch, A. ID - 15763 T2 - In Proceedings GFKL-2011, Conference of the German Classification Society, Frankfurt Germany TI - Local clique merging: An extension of the maximum common subgraph measure with applications in structural bioinformatics, Algorithms from and for Nature and Life ER - TY - CONF AU - Fallah Tehrani, A. AU - Hüllermeier, Eyke ED - Montero, J. ED - Pasi, G. ED - Ciucci, D. ID - 15112 T2 - in Proceedings EUSFLAT-2013 8th International Conference on the European Society for Fuzzy Logic and Technology, Milano, Italy TI - Ordinal Choquistic regression ER - TY - CONF AU - Nasiri, N. AU - Fober, T. AU - Senge, Robin AU - Hüllermeier, Eyke ID - 15113 T2 - in Proceedings IFSA-2013 World Congress of the International Fuzzy Systems Association, Edmonton, Canada TI - Fuzzy Pattern Trees as an alternative to rule-based fuzzy systems: Knowledge-driven, data-driven and hybrid modeling of colour yield in poyester dyeing, Edmonton, Canada ER - TY - JOUR AU - Heider, D. AU - Senge, Robin AU - Cheng, W. AU - Hüllermeier, Eyke ID - 16044 IS - 16 JF - Bioinformatics TI - Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistence prediction VL - 29 ER -