Symbolic state transducers and recurrent neural preference machines for text mining

International Journal of Approximate Reasoning - Tập 32 - Trang 237-258 - 2003
Garen Arevian1, Stefan Wermter1, Christo Panchev1
1The Informatics Centre, School of Computing and Technology, University of Sunderland, St. Peter’s Campus, St. Peter’s Way, Sunderland SR6 0DD, UK

Tài liệu tham khảo

N.M. Allinson, H. Yin, Interactive and semantic data visualisation using self-organizing maps, in: Proceedings of the IEE Colloquium on Neural Networks in Interactive Multimedia Systems, 1998 M. Balabanovic, Y. Shoham, Learning information retrieval agents: experiments with automated web browsing, in: Proceedings of the 1995 AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments, Stanford, CA, 1995 M. Balabanovic, Y. Shoham, Y. Yun, An adaptive agent for automated web browsing, Technical Report CS-TN-97-52, Stanford University, 1997 T. Briscoe, Co-evolution of language and of the language acquisition device, in: Proceedings of the Meeting of the Association for Computational Linguistics, 1997 Charniak, 1993 Cleeremans, 1989, Finite-state automata and simple recurrent networks, Neural Computation, 1, 372, 10.1162/neco.1989.1.3.372 R. Cooley, B. Mobasher, J. Srivastava, Web mining: information and pattern discovery on the world wide web, in: International Conference on Tools for Artificial Intelligence, Newport Beach, CA, November 1997 M. Craven, D. DiPasquo, D. Freitag, A. McCallum, T. Mitchell, K. Nigam, S. Slattery, Learning to extract symbolic knowledge from the world wide web, in: Proceedings of the 15th National Conference on Artificial Intelligence, Madison, WI, 1998 H. Cunningham, Y. Wilks, R. Gaizauskas, New methods, current trends and software infrastructure for NLP, in: Proceedings of the NEMLAP-2, Ankara, 1996 J.L. Elman, Finding structure in time, Technical Report CRL 8901, University of California, San Diego, CA, 1988 Freitag, 1998, Information extraction from html: application of a general machine learning approach, 517 C. Lee Giles, B.G. Horne, T. Lin, Learning a class of large finite state machines with a recurrent neural network, Technical Report UMIACS-TR-94-94, NEC Research Institute, Princeton, NJ, August 1994 Honkela, 2000, Self-organizing maps in symbol processing T. Joachims, Text categorization with support vector machines: learning with many relevant features, in: Proceedings of the European Conference on Machine Learning, Chemnitz, Germany, 1998 Jordan, 1986, Attractor dynamics and parallelism in a connectionist sequential machine, 531 Kaski, 1998, WEBSOM – self-organizing maps of document collections, Neurocomputing, 21, 101, 10.1016/S0925-2312(98)00039-3 Kohonen, 1995 Kohonen, 1998, Self-organisation of very large document collections: state of the art, 65 Kremer, 1995, On the computational power of Elman-style recurrent networks, IEEE Transactions on Neural Networks, 6, 1000, 10.1109/72.392262 Yann le Cun, Une procédure d’apprentissage pour réseau à seuil assymétrique, in: Cognitiva 85: A la Frontière de l’Intelligence Artificielle des Sciences de la Connaissance des Neurosciences, Paris, CESTA, 1985, pp. 599–604 D.D. Lewis, Reuters-21578 text categorization test collection, 1997. Available from http://www.research.att.com/∼lewis F. Menczer, R. Belew, W. Willuhn, Artificial life applied to adaptive information agents, in: Proceedings of the 1995 AAAI Spring Symposium on Information Gathering from Heterogeneous, Distributed Environments, 1995 Niki, 1997, Self-organizing information retrieval system on the web: SirWeb, vol. 2, 881 C.W. Omlin, C. Lee Giles, Constructing deterministic finite-state automata in recurrent neural networks, Technical Report 94-3, Computer Science Department, Rensselaer Polytechnic Institute, Troy, NY 12180, 1994 Papka, 1997, Text-based information retrieval using exponentiated gradient descent, vol. 9 D.B. Parker, Learning-logic, Technical Report TR-47, Sloan School of Management, MIT, Cambridge, MA, 1985 M. Perkowitz, O. Etzioni, Adaptive web sites: an AI challenge, in: International Joint Conference on Artificial Intelligence, Nagoya, Japan, 1997 Rumelhart, 1986, Learning internal representations by error propagation, vol. 1, 318 M. Sahami, M. Hearst, E. Saund, Applying the multiple cause mixture model to text categorization, Technical Report, AAAI Spring Symposium on Machine Learning in Information Access, 1996 Salton, 1989 H. Schuetze, D.A. Hull, J.O. Pedersen, A comparison of classifiers and document representations for the routing problem, in: Proceedings of the Special Interest Group on Information Retrieval, 1995 D. Servan-Schreiber, A. Cleeremans, J.L. McClelland, Encoding sequential structure in simple recurrent networks, Technical Report CMU-CS-88-183, Carnegie Mellon University, Pittsburgh, PA, 1988 Sharkey, 1996, Separating learning and representation, 17 Sun, 1999, Multi-agent reinforcement learning: weighting and partitioning, Neural Networks, 10.1109/IJCNN.1999.833414 van Noord, 1997, FSA utilities: a toolbox to manipulate finite-state automata, vol. 1260, 87 P.J. Werbos, Beyond regression: new tools for regression and analysis in the behavioral sciences, Ph.D. Thesis, Harvard University, Division of Engineering and Applied Physics, 1974 S. Wermter, Hybrid Connectionist Natural Language Processing, Chapman & Hall, Thomson International, London, UK, 1995 Wermter, 1999, Preference Moore machines for neural fuzzy integration, 840 Wermter, 2000, Neural fuzzy preference integration using neural preference moore machines, International Journal of Neural Systems, 10, 287, 10.1142/S0129065700000259 Wermter, 1999, Recurrent neural network learning for text routing, 898 Wermter, 2000, Network analysis in a neural learning internet agent, 880 Wermter, 1999, Hybrid neural plausibility networks for news agents, 93 Wermter, 2000