Prof. Dr. Stefan Wermter
Head of Knowledge Technology
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Contact Info |
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| Address: | University of Hamburg Department of Computer Science Knowledge Technology, WTM, Haus F Vogt Koelln Str. 30 22527 Hamburg Germany |
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| Office: | F-230 | |
| Phone: | +49 40 428 83 2434 | |
| Fax: | +49 40 428 83 2515 | |
| Secretary: | +49 40 428 83 2433 | |
| Email: | wermter at informatik dot uni-hamburg dot de | |
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Click on the Quick links below:
- Research Interests
- Short Curriculum Vitae
- Research Projects
- PhD Student Supervision
- Editorial Boards /Committees
- Job Openings and Topics
- Teaching
- Organised Events
- Book Reviews
- Books and Theses
- Journals and Book Chapters
- Refereed Proceedings
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Research Interests
- Knowledge Representation, Neural Networks, Natural Computation, Multimodal Integration, Hybrid Integration of different symbolic and neural Representations, Cognitive Robotics, Artificial Intelligence, Cognitive Neuroscience, Natural Language Processing, Data and Text Mining, Machine Learning.
- Our objective in Knowledge Technology is to research into the foundations, representations and applications of hybrid intelligent systems. Our research is often motivated by natural systems, e.g. biology, cognition and the human brain. We want to exploit these foundations in order to build more sophisticated next-generation knowledge-based reasoning systems, adaptive human computer interaction systems, learning agents, self organising information systems and robotic engineering systems. For building such nature-inspired knowledge-based systems we integrate formal, neural, statistical and/or symbolic representations into knowledge-based learning agents. Applications include medical reasoning under uncertainty, intelligent retrieval systems, interactive systems, adaptive engineering, data/text mining systems, cognitive and neuroscience-inspired robots, speech/language systems, intelligent web agents and hybrid techniques for medical diagnosis.
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Short Curriculum Vitae
- Diplom, Department of Computer Science, University of Dortmund, Germany (1987)
- Award Fellowship of the German Academic Exchange Service, Department of Computer Science, University of Massachusetts at Amherst, USA (1987-1988)
- Research Assistant, Department of Computer Science, University of Massachusetts, USA (1988-1989)
- Master of Science, Department of Computer Science, University of Massachusetts, USA (1989)
- Research Associate and Lecturer, Department of Computer Science, University of Dortmund, Germany (1990-1991)
- PhD, Department of Computer Science, University of Hamburg, Germany (1993)
- Research Scientist, Department of Computer Science, University of Hamburg, Germany; leading working group on hybrid neural processing (1991-1997)
- Visiting Research Scientist, International Computer Science Institute, Berkeley, California, USA (1997)
- Higher Doctorate (Habilitation), Department of Computer Science, University of Hamburg, Germany. Learning of robust language processing in hybrid neural architectures (1998)
- Professor of Computer Science, Chair for Intelligent Systems, School of Computing and Technology, University of Sunderland, England (1998-2010)
- Professor of Computer Science, Chair for Knowledge Technology, Department of Computer Science, University of Hamburg, Germany (2010-)
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Research Projects
Recently I have coordinated or participated in a number of projects, including:
- Robotics for the Development of Cognition (RobotDoc)
- Knowledgeable SErvice Robots for Aging (KSERA)
- What it means to communicate (NESTCOM)
- Midbrain Computational and Robotic Auditory Model for focused Hearing (MiCRAM)
- Biomimetic Multimodal Learning in a Mirror Neuron-based Robot (MirrorBot)
- Emerging computational neural architectures based on neuroscience (EmerNet)
- Experimental and Neurocomputational Investigations of Cognitive Systems (ENICS)
- Towards helpdesk automation using scanning language understanding and hybrid neural language techniques (HelpNet)
- Localising and Tracking Sound in a neurally inspired robot (TRACKBOT)
- European Network Robotics Network of Excellence (Partner member in EURON2)
- Hybrid neural intelligent agents (HyNeT)
- Hybrid systems and hybrid Methodology (HyM)
- Hybrid neural spoken language systems (SCREEN)
- Hybrid neural, rule-based and case-based eValuation (HyValue)
- Formal unification for language processing (Vesuv)
A list of current and recent project can be found at the Project page of the Knowledge Technology research group.
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PhD Student Supervision
Completed and awarded (only recent ones since 2002):
- Ken McGarry - Rule extraction and knowledge transfer from radial basis function neural networks (2003)
- Li Hung - An adaptive SOM model for document clustering using hybrid neural techniques (2004)
- Sheila Garfield - Hybrid processing for spoken language classification (2004)
- Stephen Womble - Temporal sequence learning from a neocortical perspective (2004)
- Christo Panchev - Spatio-temporal and multimodal processing in a spiking neural mind of a robot (2005)
- Mark Elshaw - Multimodal neural grounding of language processing for robot actions (2005)
- Dale Addison - A biologically plausible strategy for the avoidance of catastrophic interference (2005)
- John Murray - Trackbot: Acoustic tracking with a Peoplebot (2006)
- Garen Arevian - Recurrent neural networks for text classification of news articles from the Reuters Corpus (2007)
- Wolfgang Schmidle - A model of neural sequence detectors for sentence processing (2007)
- David Muse - A neural robot control architecture based on actor-critic reinforcement learning (2008)
- Abdulrahman Althahan - Variable lambda and conjugate temporal difference methods for visual robot homing (2009)
- Alan Yau Yung - A biologically inspired neural architecture for emotional robots (2010)
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Recent Activities in Editorial Boards and Programme Committees
- Board of European Neural Network Society (elected for 2007-2012 period)
- Associate Editor of Hybrid Intelligent Systems
- Associate Editor of Connection Science
- Associate Editor of Knowledge and Information Systems
- Editorial Board and Action Editor of Neural Networks
- Editorial Board of Cognitive Systems Research
- Editorial Board of International Journal of Computational Intelligence and Applications
- Editorial Board of Neural Computing Surveys
- Editorial Board of Neural Information Processing - Letters and Reviews
- Editorial Board of International Journal of Computational Intelligence
- Editorial Board of Cognitive Computation
- Member of IEEE Autonomous Mental Development Technical Committee (AMDTC) 2012
- Reviewer and Member of the EPSRC College Prioritization Panel of Engineering and Physical Sciences Research Council 2006-2010
- Invited Key note speaker at International Frontier Science Conference on Experimental Cognitive Robotics, Tokyo/Kanagawa, Japan, 2008.
- Invited Key note speaker at International Conference on Hybrid Intelligent Systems, 2005, Rio de Janeiro, Brazil
- Invited Key note speaker at International Conference on Artificial Neural Networks, 2006, Athens
- Invited Key note speaker at International Workshop on Neural Symbolic Systems, ECAI, 2006
- Invited Key note speaker at International Workshop on Neural Computation, 2004
- Recent Programme Committees
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Job Openings and Research Topics
- If you are looking for an interesting PhD research project, e.g. PhD around the following research topics, you could email. Sometimes there are a restricted number of PhD studentships available on related and other topics. Furthermore, research / training opportunities exist from the EU for European researchers as Marie Curie Fellowships at different levels: predoc, postdoc, or advanced senior researcher. We are interested to host researchers who would like to come to do research in our area.
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Teaching
I have taught mainly in the areas of:
- Knowledge Representation in Hybrid Architectures
- Algorithmic Learning
- Knowledge-based Systems
- Information Systems
- Intelligent Systems
- Neural Networks
- Hybrid Neural Symbolic Systems
- Natural Language Processing
- Artificial Intelligence
- Automatic Knowledge Acquisition
- Cognitive Robotics
- Presentation skills and thesis writing for research students
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Organised Events
- 2009 Meeting of Natural Computing Application Forum: Intelligent Robotics, organised by Stefan Wermter, Michael Knowles, Martin Page, Sunderland, UK
- 2008 International Workshop on Minds, brains, networks, communication and robots, organised by Stefan Wermter, Vittorio Gallese, Friedemann Pulvermueller, Edinburgh, Scotland
- 2007 International Workshop on what it means to communicate based on neural, cognitive and computational evidence, organised by Stefan Wermter, Vittorio Gallese, Friedemann Pulvermueller, Porto, Portugal
- 2005 International AI Workshop on Neurobotics, Ulm, Germany organised by Guenther Palm, Stefan Wermter, Mark Elshaw, Ulm, Germany
- 2000 International Workshop on Current Computational Architectures Integrating Neural Networks and Neuroscience, organized by Stefan Wermter, David Willshaw, Durham, UK
- 1999 EmerNet International Workshop on Emergent Neural Computational Architectures based on Neuroscience organized by Stefan Wermter, Jim Austin, David Willshaw, Edinburgh, Scotland
- 1999 AAAI Conference workshop on Neuroscience and Neural Computation organized by Jim Austin, Stefan Wermter, and Vasant Honavar, Orlando, USA
- 1998 Interdisciplinary conference, Hybrid Neural and Symbolic Language Processing, Invited Lecture Session, Stefan Wermter
- 1998 NIPS Conference Workshop on Neural Symbolic Integration, organised by Stefan Wermter, Ron Sun, Colorado, USA
- 1997 Workshop on Connectionist, Statistical and Symbolic Representations and Natural Language Processing, organized by Stephan Busemann, Karin Harbusch, Stefan Wermter
- 1995 International Workshop on New Approaches to Learning for Natural Language Processing, organised by Stefan Wermter, Gabriele Scheler, Ellen Riloff, Montreal, Canada
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Book reviews for Cognitive Systems Research welcome
- I am the editor for book review articles for the journal of Cognitive Systems Research. If you have recently written a book within the scope of the journal or you know of a new book within the scope of the journal you are encouraged to contact me. Also I am interested to hear from researchers who are interested to write a book review article. Further information on book review articles and a list of books can be found here.
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Books, Special Issues and Theses
S. Wermter, M. Page, M. Knowles, V. Gallese, F. Pulvermuller and J. Taylor. Neural Network: Special Issue on What it Means to Communicate. Volume 22, Number 2, March, 2009.
Wermter S., Palm G., Elshaw M. (Eds.) Biomimetic Neural Learning for Intelligent Robots. Springer, Heidelberg, Germany. 2005.
S. Wermter S., Austin J., Willshaw D. (Eds.) Emergent Neural Computational Architectures based on Neuroscience. Springer, Heidelberg, Germany, 2001
S. Wermter, R. Sun (Eds.) Hybrid Neural Systems. Springer Verlag, Heidelberg, 2000.
S. Wermter, E. Riloff, G. Scheler (Ed). Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing Springer Verlag, Berlin, 1996.
Wermter S. 1995. Hybrid Connectionist Natural Language Processing. Chapman and Hall, International Thomson Computer Press, London, UK, 1995.
Wermter S. Learning of Robust Language Processing in Hybrid Connectionist Architectures. Higher Doctorate (Habilitation) thesis. Department of Computer Science, University of Hamburg, Hamburg, Germany. 1998. (in German) 302pp.
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| Wermter S. A Hybrid Connectionist Approach for a Scanning Understanding of Natural Language Phrases. Doctoral thesis, Department of Computer Science, University of Hamburg, Hamburg, Germany. 1993. |
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Journals and Book Chapters
Yan, W., Meins, N., Torta, E., Weber, C., van der Pol, D., Cuipers, R.H., Wermter, S. Learning Robot Vision for Assisted Living. In Garcia-Rodriguez, J., Cazorla, M.Robotic Vision: Technologies for Machine Leaning and Vision Applications, pp. 257-280, Hershey, USA, 2013. Copyright 2013, IGI Global, www.igi-global.com. Posted by permission of the publisher.
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Navarro, N., Weber, C., Schroeter, P., Wermter, S. Real-world reinforcement learning for autonomous humanoid robot docking. Robotics and Autonomous Systems, Vol. 60(11), pp. 1400-1407, 2012.
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Yan, W., Weber, C., Wermter, S. A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera. Ambient Intelligence and Smart Environments, Vol. 3(3), pp. 237-252, 2011.
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Tripathi, N., Oakes, M., Wermter, S. Semantic subspace learning for text classification using hybrid intelligent techniques. International Journal of Hybrid Intelligent Systems, Vol. 8(2), pp. 99-114, 2011.
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Liu J., Perez-Gonzalez D., Rees A., Erwin H., Wermter S. A biologically inspired spiking neural network model of the auditory midbrain for sound source localisation. Neurocomputing. Vol. 74, pp. 129-139, 2010. (Elsevier)
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Ravulakollu, K., Knowles, M., Liu, J., Wermter, S. Towards Computational Modelling of Neural Multimodal Integration Based on the Superior Colliculus Concept. Innovations in Neural Information Paradigms and Applications, Volume 247, Springer Berlin / Heidelberg, pp. 269-291, 2009
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Muse, D., Wermter, S. Actor-Critic Learning for Platform-Independent Robot Navigation. Cognitive Computation, Volume 1(3), Springer New York, pp. 203-220, 2009
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Wermter, S., Page, M., Knowles, M., Gallese, V., Pulvermüller, F., Taylor, J. Multimodal communication in animals, humans and robots: An introduction to perspectives in brain-inspired informatics. Neural Networks 22 (2) pp. 111-115. www.elsevier.com/locate/neunet. 2009.
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Murray, J., Erwin H., and Wermter S. Robotic sound-source localisation architecture using cross-correlation and recurrent neural networks. Neural Networks 22 (2) pp. 173-189. www.elsevier.com/locate/neunet. 2009.
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| Wermter, S. and HIS group. Hybrid Intelligent Systems. NETWorks - The Science Engineering and Technology magazine for North East England. Medical Devices and Instrumentation. Issue 5, pp.14-15, Spring, 2008.
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| Hung, C. and Wermter, S. A novel self-organising clustering model for time-event documents. The Electronic Library, vol. 26, no. 2, pp. 260-272. 2008, SSCI.
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| N. Bellotto, K. Burn, E. Fletcher, and S. Wermter. Appearance-based localization for mobile robots using digital zoom and visual
compass, Robotics and Autonomous Systems, Vol. 56, Issue 2, pp. 143-156, February 2008.
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| C. Weber, M. Elshaw, S. Wermter, J. Triesch and C. Willmot. Reinforcement Learning Embedded in Brains and Robots, In: Weber, C.,
Elshaw M., and Mayer N. M. (Eds.) Reinforcement Learning: Theory and Applications. pp. 119-142, 2008, I-Tech Education and Publishing,
Vienna, Austria.
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| Weber, C., Elshaw, M., Triesch, J. and Wermter, S. Neural Control of Actions Involving Different Coordinate Systems. In Hackel, M., Humanoid Robots: Human-like Machines, pp. 577-600, Itech, Vienna, Austria, June 2007.
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| Weber C., Wermter S. A Self-Organizing Map of Sigma-Pi Units. Neurocomputing. Vol. 70, pp. 2552-2560, 2007 (Elsevier)
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| Garfield S., Wermter S., Call Classification using Recurrent Neural Networks, Support Vector Machines and Finite State Automata. Knowledge and Information Systems: An International Journal, Vol 9,2, pp. 131-156 2006.
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| Panchev C., Wermter S., Temporal Sequence Detection with Spiking Neurons: Towards Recognizing Robot Language Instruction. Connection Science, Vol 18,1, pp. 1-22, 2006.
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| Muse D., Weber C., and Wermter, S. Robot Docking Based on Omnidirectional Vision and Reinforcement Learning. Knowledge-Based Systems, Vol 19, 5, pp. 324-332 2006. (Elsevier)
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| Weber C., Muse D., Elshaw M., and Wermter, S. A Camera-Direction Dependent Visual-Motor Coordinate Transformation for a Visually Guided Neural Robot. Knowledge-Based Systems, 19(5), 348-355, 2006. (Elsevier)
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| Weber C., Wermter S., and Elshaw M. A hybrid generative and predictive model of the motor cortex. Neural Networks, Vol. 19(4), pp. 339-353. 2006.
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| Malone J., McGarry K., Wermter S., and Bowerman C. Data mining using rule extraction from Kohonen self-organising maps,
Neural Computing Applications, Vol. 15 (1), pp. 9-17, 2006.
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| Garfield S., Wermter S., and Devlin S. Spoken Language Classification using Hybrid Classifier Combination. International Journal of Hybrid Intelligent Systems Vol. 2, No.1, pp.13-33, 2005.
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| Chokshi K., Wermter S., Panchev C., Burn K. Image Invariant Robot Navigation Based on Self Organising Neural Place Codes. In
Wermter S., Palm G., Elshaw M., Biomimetic Neural Learning for Intelligent Robots, pp.74-88, 2005.
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| Murray J., Erwin H., Wermter S. A Hybrid Architecture using Cross-Correlation and Recurrent Neural Networks for Acoustic Tracking in Robots. In Wermter S., Palm G., Elshaw M., Biomimetic Neural Learning for Intelligent Robots, pp. 55-73, 2005.
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| Wermter S., Weber C., Elshaw M., Gallese, V. Pulvermüller F. Grounding Neural Robot Language in Action. In Wermter S., Palm G., Elshaw M. Biomimetic Neural Learning for Intelligent Robots, pp. 162-181, 2005.
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| Wermter S., Palm G., Weber C., Elshaw M. Towards Biomimetic Neural Learning for Intelligent Robots. In Wermter S., Palm G., Elshaw M., Biomimetic Neural Learning for Intelligent Robots, pp. 1-18, 2005.
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| Wermter S., Weber C., Elshaw M., Associative Neural Models for Biomimetic Multi-modal Learning in a Mirror Neuron-based Robot. In Cangelosi A., Bugmann G. Borisyuk R. (Eds.), Modeling Language, Cognition and Action. Singapore: World Scientific. pp. 31-46, 2005.
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| Hung C., Wermter S. Neural Network-based Document Clustering using WordNet Ontologies. International Journal of Hybrid Intelligent Systems, Vol. 1, pp. 127-142, 2004.
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| Cox, S., Oakes, M., Wermter, S.and Hawthorne, M, AudioMine: Medical Data Mining in Heterogeneous Audiology Records. International Journal of Computational Intelligence, Vol. 1, pp. 1-12, 2004.
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| Weber C., Wermter S., Zochios A. Robot Docking with Neural Vision and Reinforcement. Knowledge Based Systems, Vol. 12, No. 2-4, pp. 165-72, 2004.
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| Panchev C., Wermter S., Spike-timing-dependent Synaptic Plasticity: From Single Spikes to Spike Trains. Neurocomputing, Vol. 58-60, pp. 365-371, 2004.
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| Wermter S., Weber C., Elshaw M., Panchev C., Erwin H., Pulvermüller F., Towards Multimodal Neural Robot Learning. Robotics and Autonomous Systems Journal, Vol. 47, No. 2-3, pp. 171-175, 2004.
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| Hung C., Wermter S., Smith P. Hybrid Neural Document Clustering Using Guided Self-organisation and WordNet.IEEE Intelligent Systems. pp. 68-77, March/April 2004. 2004 IEEE.
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| Garfield, S, Wermter S., Recurrent Neural Learning for Classifying Spoken Utterances. Expert Update, Special Issue on Neural Language Processing, Vol. 6, No. 3, pp. 31-36. 2003.
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| Arevian G., Wermter S., Panchev C. Symbolic State Transducers and Recurrent Neural Preference Machines for Text Mining. International Journal on Approximate Reasoning, Vol. 32, No. 2/3, pp. 237-258, 2003. Elsevier.
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| Wermter S., Elshaw M., Farrand S. A Modular Approach to Self-organisation of Robot Control Based on Language Instruction. Connection Science, Vol. 15, No 2-3, pp. 73-94, 2003.
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| Wermter S., Elshaw M. Learning Robot Actions Based on Self-organising Language Memory. Neural Networks, Vol. 16, No. 5-6, pp. 691-699, 2003.
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| Wermter S., Panchev C. Hybrid Preference Machines based on Inspiration from Neuroscience. Cognitive Systems Research. Vol. 3, No. 2, pp. 255-270, 2002. Elsevier.
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| Womble, S., Wermter S. Mirror Neurons and Feedback Learning. In Stamenov, M. I. and Gallese, V. Mirror Neurons and the Evolution of Brain and Language. John Benjamins Publishing Company, Amsterdam, pp. 353-362, 2002.
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| McGarry K., Wermter S., MacIntyre J. The Extraction and Comparison of Knowledge From Local Function Networks International Journal of Computational Intelligence and Applications, Vol. 1 Issue 4, pp: 369-382, 2001.
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| Wermter S., Austin J., Willshaw D., Elshaw M. Towards Novel Neuroscience-inspired Computing. In Wermter S., Austin J. and Willshaw D. Emergent Neural Computational Architectures based on Neuroscience. Springer, Heidelberg, Germany. pp. 1-19, 2001.
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| Wermter S., Sun R. The Present and the Future of Hybrid Symbolic Systems. AI Magazine. Spring, pp. 123-126. 2001.
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| Wermter S. The Hybrid Approach to Artificial Neural Network-based Language Processing. In: Dale R., Moisl H. and Somers H. (Ed.) Handbook of Natural Language Processing. p. 823-846. Marcel Dekker. 2000.
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| Wermter S. Neural Network Agents for Learning Semantic Text Classification. Information Retrieval. Vol. 3, No. 2, p. 87-103. 2000.
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| Wermter S. Neural Fuzzy Preference Integration using Neural Preference Moore Machines. International Journal of Neural Systems. Vol. 10, No. 4, pp. 287-309, 2000.
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| Wermter S. Knowledge Extraction from Transducer Neural Networks. Journal of Applied Intelligence. Vol. 12, p. 27-42. 2000.
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| Wermter S., Arevian G., Panchev C. Towards Hybrid Neural Learning Internet Agents. In: Wermter S., Sun R. (Ed.) Hybrid Neural Systems. p. 160-176. Springer, Heidelberg, Germany. 2000.
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| McGarry K., Wermter S., MacIntyre J. Hybrid Neural Systems: From Simple Coupling to Fully Integrated Neural Networks. Neural Computing Surveys. Vol. 2. p. 62-94. 1999.
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| Wermter S., Weber, V. SCREEN: Learning a Flat Syntactic and Semantic Spoken Language Analysis Using Artificial Neural Networks. Journal of Artificial Intelligence Research. Vol. 6, No. 1, p. 35-85. 1997.
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| Wermter S., Hannuschka R. A Connectionist Model for the Interpretation of Metaphors. In: Dorffner G. (Ed.) Neural Networks and a New AI. p. 255-276, Thomson International, London, UK. 1997.
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| Wermter S., Weber, V. Interactive Spoken-Language Processing in a Hybrid Connectionist System SCREEN. IEEE Computer Journal. p. 65-74, July 1996.
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| Weber V., Wermter S. Using Hybrid Connectionist Learning for Speech/Language Analysis. In S. Wermter, E. Riloff, G. Scheler (Ed.) Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing. p. 87-101, Springer Verlag, Berlin. 1996.
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| Weber V., Wermter S. Towards Learning Semantics of Spontaneous Dialog Utterances in a Hybrid Framework. In: J. Hallam (Ed.) Hybrid Problems, Hybrid Solutions, p. 229-238, IOS Press, Amsterdam. 1995.
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| Wermter S., Lehnert W. G. A Parallel Model for Compositional Similarity of Natural Language Concepts. In: Hahn U., Adriaens G. (Eds.) Parallel Natural Language Processing. Ablex Publishers, Norwood, NJ. 1994.
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| Wermter S. 1993. Konnektionistische/Hybride Verarbeitung Natürlicher Sprache. Künstliche Intelligenz. Vol. 93, No. 1, p. 42-44.
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| Wermter S., Lehnert W. G. 1992. Noun Phrase Analysis with Connectionist Networks. In: Reilly R., Sharkey N. (Eds.) Connectionist Approaches to Language Processing, p. 75-95, Lawrence Erlbaum Associates, Hillsdale, NJ.
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| Wermter S., Lehnert W. G. 1990. A Survey of Question Answering in Natural Language Processing. In: Zwaan R. A., Meutsch D. (Eds.) Computer Models and Technology in Media Research. North Holland, Amsterdam.
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| Wermter S., Lehnert W. G. A Hybrid Symbolic/Connectionist Model for Noun Phrase Understanding. Connection Science. Vol. 1 No. 3, p. 255-272. 1989.
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