
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
Vassilios Petridis, Vassilis G. Kaburlasos, "Clustering and Classification in Structured Data Domains Using Fuzzy Lattice Neurocomputing (FLN)," IEEE Transactions on Knowledge and Data Engineering, vol. 13, no. 2, pp. 245260, March/April, 2001.  
BibTex  x  
@article{ 10.1109/69.917564, author = {Vassilios Petridis and Vassilis G. Kaburlasos}, title = {Clustering and Classification in Structured Data Domains Using Fuzzy Lattice Neurocomputing (FLN)}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {13}, number = {2}, issn = {10414347}, year = {2001}, pages = {245260}, doi = {http://doi.ieeecomputersociety.org/10.1109/69.917564}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Knowledge and Data Engineering TI  Clustering and Classification in Structured Data Domains Using Fuzzy Lattice Neurocomputing (FLN) IS  2 SN  10414347 SP245 EP260 EPD  245260 A1  Vassilios Petridis, A1  Vassilis G. Kaburlasos, PY  2001 KW  Text classification KW  neural networks KW  clustering KW  graphs KW  framework of fuzzy lattices. VL  13 JA  IEEE Transactions on Knowledge and Data Engineering ER   
Abstract—A connectionist scheme, namely, σ
[1] L.D. Baker and A.K. McCallum, “Distributional Clustering for Text Classification,” Proc. 21st Ann. Int'l ACM SIGIR Conf. Research and Development in Information Retrieval, 1998.
[2] G. Birkhoff, Lattice Theory. Providence, R.I.: Am. Math. Soc., Colloquium Publications, vol. 25, 1967.
[3] G. Carpenter and S. Grossberg, “A Massively Parallel Architecture for a SelfOrganizing Neural Pattern Recognition Machine,” Computer Vision, Graphics and Image Understanding, vol. 37, pp. 54–115, 1987.
[4] G.A. Carpenter, S. Grossberg, and D.B. Rosen, “Fuzzy ART: Fast Stable Learning and Categorization of Analog Patterns by an Adaptive Resonance System,” Neural Networks, vol. 4, pp. 759–771, 1991.
[5] C.H. Chang and C.C. Hsu, “Enabling ConceptBased Relevance Feedback for Information Retrieval on the WWW,” IEEE Trans. Knowledge and Data Eng., vol. 11, no. 4, pp. 595–609, 1999.
[6] W.W. Cohen, “Learning Trees and Rules with SetValued Features,” 1996 AAAI Proc. Thirteen Nat'l Conf. Artificial Intelligence, Aug. 1996.
[7] H. Drucker, D. Wu, and V.N. Vapnik, “Support Vector Machines for Spam Categorization,” IEEE Trans. Neural Networks, vol. 10, no. 5, pp. 1048–1054, 1999.
[8] P. Frasconi, M. Gori, and A. Sperduti, “A General Framework for Adaptive Processing of Data Structures,” IEEE Trans. Neural Networks, vol. 9, no. 5, pp. 768–786, 1998.
[9] M. Georgiopoulos, H. Fernlund, G. Bebis, and G.L. Heileman, “Order of Search in Fuzzy ART and Fuzzy ARTMAP: Effect of the Choice Parameter,” Neural Networks, vol. 9, no. 9, pp. 1541–1559, 1996.
[10] M. Gori and F. Scarselli, “Are Multilayer Perceptrons Adequate for Pattern Recognition and Verification?” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 11, pp. 1121–1132, 1998.
[11] S.J. Green, “Building Hypertext Links by Computing Semantic Similarity,” IEEE Trans. Knowledge and Data Eng., vol. 11, no. 5, pp. 713–730, 1999.
[12] L. Guersey, “The Search Engine as Cyborg,” New York Times, (06/29/00), P.E1.
[13] J. Huang, M. Georgiopoulos, and G.L. Heileman, “Fuzzy ART Properties,” Neural Networks, vol. 8, no. 2, pp. 203–213, 1995.
[14] M. Junker and A. Abecker, “Exploiting Thesaurus Knowledge in Rule Induction for Text Classification,” Proc. Recent Advances in Natural Language Processing (RANLP '97), pp. 202–207, 1997.
[15] V.G. Kaburlasos and V. Petridis, “Fuzzy Lattice Neurocomputing (FLN): A Novel Connectionist Scheme for Versatile Learning and Decision Making by Clustering,” Int'l J. Computers and Their Applications, vol. 4, no. 2, pp. 31–43, 1997.
[16] V.G. Kaburlasos and V. Petridis, “Fuzzy Lattice Neurocomputing (FLN) Models,” Neural Networks, vol. 13, no. 10, pp. 11451170, 2000.
[17] S. Lawrence and C.L. Giles, “Searching the World Wide Web,” Science, vol. 280, pp. 98–100, Apr. 1998.
[18] Y. Lecun, L. Bottou, Y. Bengio, and P. Haffner, “GradientBased Learning Applied to Document Recognition,” Proc. IEEE, vol. 86, no. 11, pp. 2278–2324, 1998.
[19] D.D. Lewis Professional Home Page for David D. Lewis of AT&T Labs—Research,http://www.research.att.com~lewis.
[20] D. Mladenic, “Machine Learning on Nonhomogeneous, Distributed, Text Data,” PhD dissertation, Dept. Computer and Information Science, Univ. of Ljubljana, Slovenia, 1998.
[21] D. Mladenic, “TextLearning and Related Intelligent Agents: A Survey,” IEEE Intelligent Systems, vol. 14, no. 4, pp. 44–54, 1999.
[22] MOBY Thesaurus,http://www.dcs.shef.ac.uk/research/ilash/ Mobymthes.html.
[23] C.W. Omlin and C.L. Giles, “Constructing Deterministic FiniteState Automata in Recurrent Neural Networks,” J. ACM, vol. 43, no. 6, pp. 937–972, 1996.
[24] V. Petridis and V.G. Kaburlasos, “Fuzzy Lattice Neural Network (FLNN): A Hybrid Model for Learning,” IEEE Trans. Neural Networks, vol. 9, no. 5, pp. 877–890, 1998.
[25] V. Petridis and V.G. Kaburlasos, “Learning in the Framework of Fuzzy Lattices,” IEEE Trans. Fuzzy Systems, vol. 7, no. 4, pp. 422–440, 1999, errata in IEEE Trans. Fuzzy Systems, vol. 8, no. 2, p. 236, 2000.
[26] T.A. Plate, “Holographic Reduced Representations,” IEEE Trans. Neural Networks, vol. 6, no. 3, pp. 623–641, 1995.
[27] J.B. Pollack, “Recursive Distributed Representations,” Artificial Intelligence, vol. 46, nos. 12, pp. 77–106, 1990.
[28] M. Porter, The‘Official’home page for distribution of the Porter Stemming Algorithm,http://www.muscat.com/~martinstem.html.
[29] D.E. Rumelhart and J.L. McClelland, “On Learning the Past Tenses of English Verbs,” Parallel Distributed Processing; Volume 2: Psychological and Biological Models, J.L. McClelland, D.E. Rumelhart, and the PDP Research Group, eds., Cambridge, Mass.: MIT Press, pp. 216–271, 1986.
[30] J.R. Quinlan, C4.5: Programs for Machine Learning,San Mateo, Calif.: Morgan Kaufman, 1992.
[31] M. Sahami, “Using Machine Learning to Improve Information Access,” PhD dissertation, Dept. Computer Science, Stanford Univ., 1998.
[32] F. Scarselli and A.C. Tsoi, “Universal Approximation Using Feedforward Neural Networks: A Survey of Some Existing Methods, and Some New Results,” Neural Networks, vol. 11, no. 1, pp. 15–37, 1998.
[33] A. Sperduti, A. Starita, and C. Goller, “Learning Distributed Representations for the Classification of Terms,” Proc. Int'l Joint Conf. Artificial Intelligence, pp. 509–515, 1995.
[34] A. Sperduti and A. Starita, “Supervised Neural Networks for the Classification of Structures,” IEEE Trans. Neural Networks, vol. 8, no. 3, pp. 714–735, 1997.
[35] D. Touretzky, “BoltzCONs: Reconciling Connectionism with the Recursive Nature of Stacks,” Connectionist Symbol Processing, G. Hinton, ed., Cambridge, Mass.: MIT Press, 1991.
[36] S.M. Weiss, C. Apte, F.J. Damerau, D.E. Johnson, F.J. Oles, T. Goetz, and T. Hampp, “Maximizing TextMining Performance,” IEEE Intelligent Systems, vol. 14, no. 4, pp. 63–69, 1999.