Alfredo Vellido / citations
Vellido, A., (2006) Missing data imputation through GTM as a mixture of t-distributions. Neural Networks, Neural Networks, 19(10), 1624-1635.
1. [SELF-CITATION] On the improvement of brain tumour data clustering using class information. In Proc. of the 3rd European Starting AI Researcher Symposium (STAIRS'06), Riva del Garda, Italy.
Cruz, R., Vellido, A.
Andrade, A.O. and Vellido, A. (2006) Determining feature relevance for the grouping of motor unit action potentials through Generative Topographic Mapping. In Proc. of the IASTED 25th Int. Conf. Modelling, Identification, and Control, MIC’06, Lanzarote, Spain, 2006, 507-512.
1. [SELF-CITATION] Assessment of an Unsupervised Feature Selection Method for Generative Topographic Mapping, In Proc. of the 16th International Conference on Artificial Neural Networks (ICANN 2006), Athens, Greece.
Vellido, A.
Vellido,
A., Lisboa, P.J.G. and Vicente, D. (2006) Robust analysis of MRS
brain tumour data using t-GTM. Neurocomputing, 69(7-9), March
2006, 754-768.
1. [SELF-CITATION] Determining feature relevance for the grouping of motor unit action potentials through Generative Topographic Mapping.
In Proc. of the IASTED 25th Int. Conf. Modelling, Identification, and Control, MIC’06, Lanzarote, Spain, 2006, 507-512.
Andrade, A.O. and Vellido, A.
2. [SELF-CITATION] Characterization of atypical virtual campus usage behavior through robust generative relevance analysis,
In Proc. of the 5th IASTED Int. Conf. on Web-Based Education (WBE 2006), Puerto Vallarta, México, 2006, 183-188.
Vellido, A., Castro, F., Nebot, A., and Múgica, F.
3. [SELF-CITATION] Assessment of an Unsupervised Feature Selection Method for Generative Topographic Mapping, In Proc. of the 16th International Conference on Artificial Neural Networks (ICANN 2006), Athens, Greece.
Vellido, A.
Vellido, A. and Lisboa, P.J.G. (2006) Handling outliers in brain tumour MRS data analysis through robust topographic mapping, Computers in Biology and Medicine, In press.
1. [SELF-CITATION] Determining feature relevance for the grouping of motor unit
action potentials through Generative Topographic Mapping. In Procs. Of the IASTED 25th
Int. Conf. Modelling, Identification, and Control, MIC’06, Lanzarote, Spain, 2006, 507-512.
Andrade, A.O. and Vellido, A.
Vellido, A., Castro, F., Nebot, A., and Múgica, F., (2006) Characterization of atypical virtual campus usage behavior through robust generative relevance analysis, In Proc. of the WBE 2006, Puerto Vallarta, México, pp.183-188.
1. [SELF-CITATION] Identification of fuzzy models to predict students performance in an e-learning environment, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.74-79.
Nebot, A., Castro, F., Múgica, F., and Vellido, A.
Vellido, A., Lisboa, P.J.G., and Vicente,D. (2005) Handling outliers and missing data in brain tumor clinical assessment usign t-GTM. In Proc. of the ESANN 2005, D-Side Pub., Bruges, Belgium, pp.121-126.
1. [SELF-CITATION] Missing data imputation through GTM as a mixture of t-distributions
Neural Networks, In Press, Available online 31 March 2006,
Vellido, A.
Vellido, A. and Lisboa, P.J.G. (2005) Functional topographic mapping for robust handling of outliers in brain tumour data, in: Proceedings of ESANN 05, D-Side Pub., Bruges, Belgium, pp. 133–138.
1. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping.
Computers in Biology and Medicine, (2006) In press.
Vellido, A. and Lisboa, P.J.G.
Olier, I. and Vellido, A. , (2005) Comparative assessment of the robustness of missing data imputation through Generative Topographic Mapping, In Proc. of the IWANN 2005, Vilanova i la Geltru, Barcelona, Spain. LNCS Vol.3512, 771-778.
1. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM
Neurocomputing, 69 (7-9), 2006, 754-768
2. [SELF-CITATION] Capturing the Dynamics of Multivariate Time Series Through Visualization Using Generative Topographic Mapping Through Time, In Proc. of the 1st IEEE International Conference on Engineering of Intelligent Systems, ICEIS'2006, Islamabad, Pakistán, pp.492-497.
Olier, I. and Vellido, A.
Castro, F. , Vellido, A. , Nebot, A. and Minguillón, J. (2005) Detecting atypical student behaviour on an e-learning system. In Proc. of SINTICE’2005, Granada, Spain, September 2005, 153-160.
1. [SELF-CITATION] Identification of fuzzy models to predict students performance in an e-learning environment, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.74-79.
Nebot, A., Castro, F., Múgica, F., and Vellido, A.
2. Educational data mining: A survey from 1995 to 2005
Expert Systems with Applications, in press.
C. Romero, S. Ventura
Vellido, A. (2005) Preliminary theoretical results on a feature relevance determination method for Generative Topographic Mapping. Technical Report LSI-05-13-R, Universitat Politècnica de Catalunya, UPC, Barcelona, Spain
1. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM
Neurocomputing, 69 (7-9), 2006, 754-768
2. [SELF-CITATION] Characterization of atypical virtual campus usage behavior through robust generative relevance analysis,
In Proc. of the 5th IASTED Int. Conf. on Web-Based Education (WBE 2006), Puerto Vallarta, México, 2006, 183-188.
Vellido, A., Castro, F., Nebot, A., and Múgica, F.
Vicente, D., Vellido, A., Martí, E., Comas, J., and Rodriguez-Roda, I. (2004), Exploration of the ecological status of Mediterranean rivers: Clustering, visualizing and reconstructing streams data using Generative Topographic Mapping. In W.I.T. Transactions on Information and Communication Technologies, Vol.33, 121-130.
1. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM
Neurocomputing, 69 (7-9), 2006, 754-768
2. [SELF-CITATION] Missing data imputation through GTM as a mixture of t-distributions
Neural Networks, In Press, Available online 31 March 2006,
Vellido, A.
Vellido, A. (2004) Generative Topographic Mapping as a constrained mixture of Student t-distributions: Theoretical developments. Technical Report LSI-04-44-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.
1. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping.
Computers in Biology and Medicine, (2006) In press.
Vellido, A. and Lisboa, P.J.G.
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2003) Selective smoothing of the generative Topographic Mapping. IEEE Transactions on Neural Networks, 2003
1. [SELF-CITATION] Cluster-Based Visualisation of Marketing Data
Lecture Notes in Computer Science, LNCS 3177, 2004
P.J.G. Lisboa and S. Patel
2. [SELF-CITATION] Exploration of the ecological status of Mediterranean rivers: Clustering, visualizing and reconstructing streams data using Generative Topographic Mapping.
In W.I.T. Transactions on Information and Communication Technologies, Vol.33, 2004, 121-130
Vicente, D., Vellido, A., Martí, E., Comas, J., and Rodriguez-Roda, I.
3. [SELF-CITATION]
Comparative assessment of the robustness of missing data imputation
through generative topographic mapping
Lecture Notes In Computer Science LNCS 3512, 2005, 787-794.
Olier I., Vellido A.
4. The Parameterless Self-Organizing Map Algorithm
IEEE Transactions on Neural Networks, 17(2) 2006, 305-316.
E. Berglund and J. Sitte
5. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM
Neurocomputing, 69 (7-9), 2006, 754-768
6. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping.
Computers in Biology and Medicine, (2006) In press.
Vellido, A. and Lisboa, P.J.G.
7. [SELF-CITATION] Missing data imputation through GTM as a mixture of t-distributions
Neural Networks, In Press, Available online 31 March 2006,
Vellido, A.
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2002) Characterizing and Segmenting the On-Line Customer Market Using Neural Networks. In E-Commerce and Intelligent Methods. Heidelberg: Springer-Verlag, 101-119
1. Application of Intelligent Methods in Commercial Website Marketing Strategies Development.
Information Technology and Control, 2005, 34(2), 140–144
A. Noreika
2. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping
Computers in Biology and Medicine, In press.
Vellido, A. and Lisboa, P.J.G.
Vellido, A and Lisboa, P.J.G (2001) An electronic commerce application of the Bayesian Framework for MLPs: the Effect of Marginalization and ARD. Neural Computing & Applications. 10(1)
1. Application of Bayesian Neural Networks to Biological Sequence Analysis
Ziran Zazhi, 2004, 26(2) 108-111.
邵建林 史定华 王翼飞
2. Enabling a Powerful Marine and Offshore Decision-Support Solution Through Bayesian Network Technique
Risk Analysis, 2006, 26(3), 695-721.
A. G. Eleye-Datubo, A. Wall, A. Saajedi, and J. Wang
Lisboa P.J.G, Vellido A, Wong H. (2000) Outstanding issues for clinical decision support with Neural Networks, in: Artificial Neural Networks in Medicine and Biology, Springer, London, pp. 63–71.
1. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping
Computers in Biology and Medicine, In press.
Vellido, A. and Lisboa, P.J.G.
2. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM
Neurocomputing, 69 (7-9), 2006, 754-768
Lisboa P.J.G, Vellido A, Wong H. (2000) Bias reduction in skewed binary classification with Bayesian neural networks. Neural Networks.
1. [SELF-CITATION] Are neural networks best used to help logistic regression? An example from breast cancer survival analysis
Proceedings of the International Joint Conference on Neural Networks, 2001, 2472-2477
P.J.G. Lisboa, H. Wong
2. [SELF-CITATION] A review of evidence of health benefit from artificial neural networks in medical intervention
Neural Networks, 15(1), 2002, 11-39
P.J.G. Lisboa
3. [SELF-CITATION] A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer
Artificial Intelligence in Medicine, 28(1), 2003, 1-25
P.J.G. Lisboa, H. Wong, P. Harris and R. Swindell
4. An Artificial Neural Network for Analysing the Survival of Patients with Colorectal Cancer
In Procs. of the ESANN 2005, D-Side pub., 2005, 103-108.
R. Bittern, A. Cuschieri, S.D. Dolgobrodov, R. Marshall, P. Moore, and R.J.C. Steele
5. [SELF-CITATION] The use of artificial neural networks in decision support in cancer: A systematic review
Neural Networks, 19(4), 2006, 408-415.
P.J.G. Lisboa and A.F.G. Taktak
6. e-Science and artificial neural networks in cancer management
Concurrency and Computation: Practice and Experience, 2006, in press
S.D. Dolgobrodov, R. Marshall, P. Moore, R. Bittern, R.J.C. Steele, A. Cuschieri
Vellido, A., Lisboa, P.G.J., and Meehan, K. (2000). Quantitative characterization and prediction for on-line purchasing behavior: A latent variable approach. International Journal of Electronic Commerce.
1. Differential effects of product category on shoppers’ selection of web-based stores: a probabilistic modelling approach
Journal of Electronic Commerce Research, 2(4), 2001
Oded Lowengart, and Noam Tractinsky
2. Factors Affecting e-Commerce Textbook Purchases
In Procs. of the International Association for Computer Information Systems (IACIS), Vancouver, Canada, 2001, 383-389.
Reif, H., Dillon, T.W.
3. Influence of Product Class on Preference for Shopping on the Internet
Journal of Computer-Mediated Communication, 8(1), 2002.
Tulay Girard, Ronnie Silverblatt, Pradeep Korgaonkar
4. Consumer Online Shopping Attitudes and Behavior: An Assessment of Research
Eighth Americas Conference on Information Systems, 2002, 508-517.
Li, N., and Zhang, P.
5. Insights and implications of e-service end-user adoption
Technical Report SWP 2002/65. School of Information Systems. Deakin University, 2002.
Sandhu, K, and Corbitt, B.J.
6. Exploring an understanding of web-based e-service end-user adoption
Technical Report SWP 2002/66. School of Information Systems. Deakin University, 2002.
Sandhu, K, and Corbitt, B.J.
7. Online Consumer Behavior: An
Overview and Analysis of the Literature
In Proc. of the 6th Pacific Asian Conference on Information Systems
(PACIS 2002), 813-827.
T. Kwong, C. Cheung, L. Zhu, M. Limayem, D.Viehland
8. Developing
a Measurement Instrument for Discerning Consumers’ e-Commerce Purchase
Perceptions
In Procs. of the International Association for Computer Information Systems (IACIS), Florida, USA, 2002, 151-157.
Dillon, T.W., Reif, H.
9.
Supply-side hurdles in Internet B2C e-commerce: An empirical
investigation
IEEE Transactions on Engineering Management, 50 (4), 2003,
458-469
Cheung MT, Liao ZQ
10. Web-Based Shopping: Perceptions of Website Design Factors by Online New Zealand Buyers
Massey University, Department of Commerce Working Paper Series 03.08. (2003).
Shergill, G. S. and Chen, Z.
11. Relationship of Type of Product, Shopping Orientations, and Demographics with Preference for Shopping on the Internet
Journal of Business and Psychology, 18 (1), 2003, 101-120
Tulay Girard, Pradeep Korgaonkar, and Ronnie Silverblatt
12. Electronic Commerce Customer Relationship Management: A Research Agenda
Information Technology and Management 4, 2003, 233–258
Nicholas C. Romano, jr. and Jerry Fjermestad
13. Examination of brand knowledge, perceived risk and consumers' intention to adopt an online retailer.
Total Quality Management and Business Excellence 14 (6), 2003, 677-693.
Chen, R., He, F.
14. Using brand knowledge to understand consumers' intention to adopt an online retailer
International Journal of Services, Technology and Management 4 (4-6), 2003, 464-479.
Chen, R., He, F.
15. Toward an Integrative Framework for Online
Consumer Behavior Research: A Meta-Analysis Approach,
Journal of End Use Computing, 15(4), 2003, 1-26.
Saeed, K. A., Hwang, Y., and Yi, M. Y.
16. An Exploratory Study of Operant Conditioning Theory as a
Predictor of Online Product Selection
Journal of Electronic Commerce in Organizations, 1(1), 2003,
42-54
V. Perotti, P. Sorce, S. Widrick
17.
Influencing the online
consumer's behavior: the Web experience
Internet Research: Electronic Networking Applications and Policy, 1, vol. 14(2), 2004, 111-126
Constantinides, E.
18. Online Shopping for Positive and Negative Reinforcement Products
In Mehdi Khosrow-Pour, D.B.A. (Ed.), The Social and Cognitive Impacts of e-Commerce on Modern Organizations, Chapter 1, Idea Group Inc. (2004)
Patricia Sorce, Victor Perotti, Stanley Widrick
19. A meta-analysis approach toward the development of an integrative framework for online consumer behaviour research
In M.A. Mahmood (Ed.), Advanced Topics in End User Computing (Vol.3), Idea Group Inc., 2004.
Saeed, K.A., Hwang, Y., and Yi, M.Y.
20. Identifying purchase perceptions that affect consumers’ Internet buying
In N. Shin (Ed.) Strategies for Generating E-Business Returns on Investment, Idea Group Inc., 2004, pp. 235-253.
T.W. Dillon, and H.L. Reif
21. Factors Influencing Consumers’ E-Commerce Commodity Purchases
Information Technology, Learning, and Performance Journal, 22(2), 2004, 1-12
T.W. Dillon, and H.L. Reif
22. Attitude
and age differences in online buying
International Journal of Retail & Distribution Management,
33 (2), 2005, 122-132.
Patricia Sorce, Victor Perotti, and Stanley Widrick
23. Web-based shopping: consumers’ attitudes towards online shopping in New Zealand
Journal of Electronic Commerce Research, 6 (2), 2005
Gurvinder S Shergill and Zhaobin Chen
24. A critical review of online consumer behavior: Empirical research
Journal of Electronic Commerce in Organizations, 3(4), 2005, 1-19.
Cheung, C.M.K., Chan, G.W.W., Limayem, M.
25. What Makes Customers Shop
Online?
In Electronic Customer Relationship Management, Fjermestad, J.
and Romano, N. (eds), Series of Advances in Management Information
Systems (AMIS), 2006, M.E. Sharpe.
N. Li and P. Zhang
Vellido, A. (2000) A Methodology for the Characterization of B2C E-Commerce. PhD Thesis
1. Profiling internet users based on their propensity to adopt online shopping
Asia Pacific Advances in Consumer Research, 5, 2002, 30-39
Malaika Brengman, Maggie Geuens
2. Segmenting Internet shoppers based on their Web-usage-related lifestyle: a cross-cultural validation
Journal of Business Research, 58(1), 2005, 79-88.
Malaika Brengman, Maggie Geuens, Bert Weijters, Scott M. Smith and William R. Swinyard
3. Medición de las actitudes de los internautas respecto a la compra on-line. Segmentación en base a actitudes y caracterización de los segmentos identificados.
Economic Analysis Working Papers (Edited by Association of Economists of La Coruña) Vol.4(4), 2005
Lidia Andrades Caldito
Vellido, A., Lisboa, P.J.G. and Meehan, K. (2000) The Generative Topographic Mapping as a principled model for data visualization and market segmentation: an electronic commerce case study. International Journal of Computers, Systems, and Signals. 1(2), 119-138.
1. Bibliography of Self-Organizing Map (SOM) Papers: 1998-2001 Addendum.
Neural Computing Surveys, 3, 2002, 1-156.
Merja Oja, Samuel Kaski and Teuvo Kohonen
2. [SELF-CITATION] On the improvement of brain tumour data clustering using class information. In Proc. of the 3rd European Starting AI Researcher Symposium (STAIRS'06), Riva del Garda, Italy.
Cruz, R., Vellido, A.
Vellido, A., Lisboa, P.J.G. & Meehan, K. (2000) Segmenting the e-commerce market using the Generative Topographic Mapping. In Proceedings of the MICAI-2000, 470-481. Acapulco, México.
1. Bibliography of Self-Organizing Map (SOM) Papers: 1998-2001 Addendum.
Neural Computing Surveys, 3, 2002, 1-156.
Merja Oja, Samuel Kaski and Teuvo Kohonen
Lisboa, P. J. G. and Vellido, A. (2000) Business Applications of Neural Networks. In P. J. G. Lisboa, B. Edisbury and A. Vellido (Eds.) Business Applications of Neural Networks: The State-of-the-Art of Real-World Applications, pp.vii-xxii. Singapore: World Scientific.
1. Data mining and Neural Networks from a Commercial Perspective
In Procs. of the ORSNZ Conference Twenty Naught One, University of Canterbury, Christchurch, NZ, 2001.
P.A. Cerny
2. Modelling and Trading the EUR/USD Exchange Rate: Do Neural Network Models Perform Better?
CIBEF working papers. Liverpool Business School, UK, 2002.
C.L. Dunis and M. Williams
3. [SELF-CITATION] Probability Distributions, Trading Strategies and Leverage: An Application of Gaussian Mixture Models
CIBEF working papers. Liverpool Business School, UK, 2003.
A. Lindemann, C.L. Dunis, and P.J.G. Lisboa
4. Applications of Advanced Regression Analysis for Trading and Investment
In C.L. Dunis, P. Naim, and J. Laws (Eds.) Applied Quantitative Methods for Trading and Investment, John Wiley & Sons, 2003
C.L. Dunis and M. Williams
5. [SELF-CITATION] Probability distributions, trading strategies and leverage: an application of Gaussian mixture models
Journal of Forecasting, 23(8), 2004, 559-585.
A. Lindemann, C.L. Dunis, and P.J.G. Lisboa
6. An intelligent information infrastructure to support the streamlining of integrated logistics workflow
Expert Systems, 21(3), 2004, 123-137.
G.T.S. Ho, H.C.W. Lau, W.H. Ip and A. Ning
7. [SELF-CITATION] Level estimation, classification and probability distribution architectures for trading the EUR/USD exchange rate
Neural Computing and Applications, 14(3), 2005, 256-271.
A. Lindemann, C.L. Dunis, and P.J.G. Lisboa
8. [SELF-CITATION] Probability distributions and leveraged trading strategies: an application of Gaussian mixture models to the Morgan Stanley Technology Index Tracking Fund
Quantitative Finance, 5(5), 2005, 459-474.
A. Lindemann, C.L. Dunis, and P.J.G. Lisboa
9. [SELF-CITATION] Probability distribution architectures for trading silver
Neural Network World, 15(5), 2005, 437-470.
A. Lindemann, C.L. Dunis, and P.J.G. Lisboa
10. Knowledge acquisition and revision using neural networks: an application to a cross-national study of brand image perception
Journal of the Operational Research Society, 57(3), 2006, 231-240.
Setiono, R; Pan, S-L; Hsieh, M-H; Azcarraga, A
Vellido, A., Lisboa, P.J.G., and Vaughan, J. (1999) Neural networks in business: a survey of applications (1992-1998). Expert Systems with Applications
1. [SELF-CITATION] Segmentation of the on-line shopping market using neural networks
Expert Systems with Applications, 17(4),1999, 303-314
A. Vellido, P. J. G. Lisboa and K. Meehan
2. The development of a decision model for liquidity analysis .
Expert Systems with Applications, 19(4), 2000, 271-278
Sheng-Tun Li, Li-Yen Shue
and Weissor Shiue.
3.
Developing a neural network approach for intelligent scheduling in
GUESS
Expert Systems, 17(4), 2000, 185-190.
Liebowitz J, Rodens I, Zeide J, et al.
4. Artificial neural networks in accounting and finance: modeling issues
International Journal of Intelligent Systems in Accounting, Finance & Management, 9(2), 2000, 119-144.
James R. Coakley and Carol E. Brown
5.
Bankruptcy prediction for credit
risk using neural networks: A survey and new results
IEEE Transactions on Neural Networks, 12(4), 2001, 929-935.
Atiya, A.F.
6.
The Kohonen self-organizing map:
an application to the study of strategic groups in the UK hotel
industry
Expert Systems, 18 (1), 2001, 19-31.
Curry B, Davies F, Phillips P, et al.
7. Investigating the information content of non-cash-trading index futures using neural networks
Expert Systems with Applications, 22(3), 2002, 225-234.
Tian-Shyug Lee and Nen-Jing Chen
8. Credit scoring using the hybrid neural discriminant technique
Expert Systems with Applications, 23(3), 2002, 245-254.
Tian-Shyug Lee, Chih-Chou
Chiu, Chi-Jie Lu and I-Fei Chen
9.
Design of manufacturing systems by a hybrid approach with neural
network metamodelling and stochastic local search
International Journal of Production Research, 40(1), 2002, 71-92.
Chen MC, Yang TH
10. Integration of ART2 Neural Network and Genetic K-means Algorithm for Analyzing the Browsing Paths in Electronic Commerce
In Proceedings of the 4th International Conference on Electronic Commerce (ICEC), Hong Kong, 2002.
R. J. Kuo, C. L. Liao, T.-L. Hua and C. Tua
11. Neural networks and non-linear statistical methods: an application to the modelling of price-quality relationships
Computers and Operations Research, 29(8), 2002, 951-969.
12. Evolution of Artificial Neural Networks in Business Applications: An Empirical Investigation Using a Growth Model
International Journal of Management & Decision Making, 3(1), 2002, 19-34
Quaddus, M.A., and Khan, M.S.
13. Applying neural network in hydrotreating process
World Petroleum Congress Proceedings, 2002, 13-23
Da Silva, R.M.C.F., De Oliveira, L.V., De Souza Aires, J.S.
14. Data mining by using the integration of neural network and discriminant analysis
Journal of the Chinese Institute of Industrial Engineers 19(2), 2002, 9-22.
Chiu, C.-C., Lee, T.-S., Chou, Y.-C., Lu, C.-J.
15. Construction of Enterprise Distress Diagnosis Model by Using the Integration of Neural Network and Classification and Regression Trees Approach
Web Journal of Chinese Management Review, 5(4), 2002, 55-82.
Chiu, C.-C., Chien, T.-N
16. The commercial use of segmentation and predictive modeling techniques for database marketing in the Netherlands
Decision Support Systems, 34(4), 2003, 471-481.
Peter C. Verhoef, Penny N. Spring, Janny C. Hoekstra and Peter S. H. Leeflang
17. Credit scoring and rejected instances reassigning through evolutionary computation techniques
Expert Systems with
Applications,
24(4), 2003, 433-441.
Mu-Chen Chen and Shih-Hsien Huang
18. Expert systems in business: applications and future directions for the operations researcher
Industrial Management & Data Systems, 103(5), 2003.
Metaxiotis, K; Psarras, John
19.
A neural network model for bankruptcy prediction
Dynamics of Continuous Discrete and Impulsive
Systems-Series B-Applications & Algorithms, Suppl. SI 2003, 230-237
Chen X, Qi H, Li W
20. Model Development Techniques and Evaluation Methods for Prediction and Classification of Consumer Risk in the Credit Industry
In P. Zhang (ed.). Neural Networks for Business Forecasting. IRM Press: Hershey, PA. (2003)
Nargundkar, Satish and Priestley, Jennifer
21. Assessment of Model Development Techniques and Evaluation Methods for Binary Classification in the Credit Industry
DSI 2003 National Conference, Washington DC (November 2003)
Nargundkar, Satish and Priestley, Jennifer
22. La estimación de la función educativa en valor añadido mediante redes neuronales: una aplicación para el caso español
Working paper 5. Instituto de Estudios Fiscales. Ministerio de Economía y Hacienda. España. 2003.
Daniel Santín González
23. Eficiencia Técnica y Redes Neuronales: Un Modelo para el Cálculo del Valor Añadido en Educación
Phd Thesis, Universidad Complutense de Madrid, 2003
Daniel Santín González
24. The South-East Asia Crisis, Neural Networks and Market Behavior: An Exploratory Study
Review of Pacific Basin Financial Markets and Policies, 6(3), 2003, 349-379.
C. Scott
25. The Use of a Bayesian Confidence Propagation Neural Network in Pharmacovigilance
PhD Thesis. Umea University, Sweden, (2003)
Andrew Bate
26. Artificial Neural Networks in Auditing: State of the Art
Technical report. Turku Centre for Computer Science, Finland, 2003
E. Koskivaara
27. Sawtooth feature extraction of leaf edge based on Support Vector Machine
International Conference on Machine Learning and Cybernetics 5, 2003, 3039-3044.
Qi, H.-N., Yang, J.-G.
28. Mining the customer credit using classification and regression tree and multivariate adaptive regression splines
Proceedings of the International Conference on Information and Knowledge Engineering, 2, 2003, 533-538.
29. Neural networks as a decision maker for stock trading: A technical analysis approach
International Journal of Smart Engineering System Design 5 (4), 2003, 313-325
Thawornwong, S., Enke, D., Dagli, C.
30. A survey of data mining
Journal of Southwest University for Nationalities (Natural Science Edition), 2003, 29(3), 328-330.
贺清碧 胡久永
31. Applying the Hybrid Neural Network Model to Diagnose the Enterprise Distress—Consideration of Intellectual Capital Indicator
演化式類神經網路在企業危機診斷 上之應用—智慧資本指標的考量, 2004, 1-22.
Chih-Chou Chiu Te-Nien Chien Ling-Jing Kao
32. Visualization of patterns in accounting data with Self-Organizing Maps
In A. Anandarajan, C.A. Srinivasan, and M. Anandarajan (Eds.) Business Intelligence Techniques, Springer, 2004, 133-148
E. Koskivaara
33. Artificial Neural Networks for Analytical Review in Auditing
PhD thesis, Turku School of Economics and Business Administration, 2004
E. Koskivaara
34.
The adaptive selection of
financial and economic variables for use with artificial neural
networks
Neurocomputing,
56, 2004, 205-232.
Suraphan Thawornwong and David Enke
35. Modeling consideration sets and brand choice using artificial neural networks
European Journal of
Operational Research,
154(1), 2004, 206-217
Björn Vroomen, Philip Hans Franses and Erjen van Nierop
36. Mining the breast cancer pattern using artificial neural networks and multivariate adaptive regression splines
Expert Systems with Applications, 27(1), 2004, 133-142
Shieu-Ming Chou, Tian-Shyug Lee, Yuehjen E. Shao and I-Fei Chen
37. Artificial neural networks in analytical review procedures
Managerial Auditing Journal, 19 (2), 2004
Koskivaara, Eija
38.
Integration of self-organizing feature maps and
genetic-algorithm-based clustering method for market segmentation
Journal of Organizational Computing and Electronic Commerce, 14
(1), 2004 , 43-60
Kuo RJ, Chang K, Chien SY
39. An integrated data mining and behavioral scoring model for analyzing bank customers
Expert Systems with Applications, 27(4), 2004, 623-633
Hsieh, N.-C.
40. Business Forecasting with Artificial Neural Networks: An Overview
In Neural Networks in Business Forecasting, Idea Group, Inc., 2004
Zhang, G.P.
41. Integration of Self-Organizing Feature Maps and Genetic-Algorithm-Based Clustering Method for Market Segmentation
Journal of Organizational Computing and Electronic Commerce, 14(1), 2004, 43–60
R.J. Kuo, K. Chang, and S.Y.Chien
42. Toward Global Optimization of Case-Based Reasoning Systems for Financial Forecasting
Applied Intelligence, 21(3), 2004, 239-249.
K.-J. Kim
43. Redes neuronales y eficiencia: aplicación al servicio de recogida de basuras
XI Encuentro de Economía Pública, Barcelona, 5-6 Febrero 2004
F.J. Delgado Rivero
44. Differential Evolution and Sparse Neural Networks
11ème Rencontre Internationale Approches Connexionnistes en Sciences Economiques et de Gestion (ACSEG), Novembre 2004, Lille, France.
P.H. Morgan
45. Applying neural networks in quality function deployment process for conceptual design
Journal of the Chinese Institute of Industrial Engineers, 21(6), 2004, 587-596
Chou, Y.-Ch.
46. Invariant Object Recognition Based on Elastic Graph Matching
Chapter 11: NORN predictor – Stock price prediction using a neural oscillatory-based recurrent network, 2004
R. Lee and J. Liu
47. The impact of political instability on the tourism industries of selected Mediterranean destinations: a neural network approach
In D. Hall (Ed.) Tourism and Transition: Governance, Transformation and Development, CABI Publishing, 2004, 147-168.
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48. Sawtooth identification and counting of leaf edge based on SVM
Proceedings of the International Conference on Artificial Intelligence, IC-AI'04, 2, 2004, 990-995.
Qi, H., Yang, J., Lin, J.
49. Mining the customer credit using artificial neural networks and multivariate adaptive regression splines
Proceedings of the International Conference on Artificial Intelligence, IC-AI'04, 1, 2004, 133-139.
Lee, T.-S., Chen, I.-F.
50. A machine learning approach to generate rules for process fault diagnosis
Journal of Chemical Engineering of Japan, 37 (6), 2004, 691-697.
Shastri, S., Lam, C.-P., Werner, B.
51. Efficiency in Public Sector: A Neural Network Approach
10th International Conference on Computing in Economics and Finance, Amsterdam, 2004
Delgado, F.J.
52. Hybrid mining approach in the design of credit scoring models
Expert Systems with Applications, 28(4), 2005, 655-665.
Hsieh, N.-C.
53. A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines
Expert Systems with Applications, 28(4), 2005, 743-752.
T.-S. Lee and I.-F. Chen
54. Measuring efficiency with neural networks. An application to the public sector
Economics Bulletin, 3(15), 2005, 1−10.
Delgado, F.J.
55. Medición de eficiencia con redes neuronales artificiales. Una explicación al servicio
de recogida de basuras.
Cuadernos de Economía y Dirección de la Empresa, 25, 2005, 53-82
Delgado, F.J.
56. The use of data mining and neural networks for forecasting stock market returns
Expert Systems with Applications, 29(4), 2005, 927-940
David Enke and Suraphan Thawornwong
57.
The evaluation of consumer
loans using support vector machines
Expert
Systems with Applications, 30(4), 2006, 772-782
Sheng-Tun Li, Weissor Shiue and Meng-Huah Huang
58. Subscription fraud
prevention in telecommunications using fuzzy rules and neural networks
Expert Systems with Applications, In Press, Uncorrected Proof,
Available online 4 October 2005.
P.A. Estévez, C.M. Held and C.A. Pérez
59. The optimisation of neural network parameters using Taguchi's design of experiments approach: An application in manufacturing process modelling.
Neural Computing and Applications, 14 (4), 2005, 337-344.
Sukthomya, W., Tannock, J.
60. Construction of clustering and classification models by integrating Fuzzy ART, CART and neural network approaches
Journal of the Chinese Institute of Industrial Engineers 22 (2), 2005, 171-188.
Chiu, C.-C., Tien, C.-C., Chou, Y.-C.
61. The training of neural networks to model manufacturing processes
Journal of Intelligent Manufacturing, 16 (1), 2005, 39-51.
Sukthomya, W., Tannock, J.
62.
Integration of self-organizing feature maps neural
network and genetic K-means algorithm for market segmentation
Expert Systems with Applications,
30(2), 2006 , 313-324.
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63. Mining the customer credit using classification and regression tree and multivariate adaptive regression splines
Computational Statistics & Data Analysis, 50(4), 2006, 1113-1130
Tian-Shyug Lee, Chih-Chou Chiu, Yu-Chao Chou and Chi-Jie Lu
64. The evaluation of consumer loans using support vector machines
Expert Systems with Applications, 30(4), 2006, 772-782.
Li, S.-T., Shiue, W., Huang, M.-H.
65. Subscription fraud prevention in telecommunications using fuzzy rules and neural networks
Expert Systems with Applications, 31(2), 2006, 337-344
Estévez, P.A., Held, C.M. and Perez, C.A.
66. The history and trend of methods of credit risk measurement
Forecasting, 25(1), 2006, 36-41
Wang, Xian-quan, Li Yi-jun
67. A short-term capacity trading method for semiconductor fabs with partnership.
Expert Systems with Applications, In press
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68. Gas-phase exposure
history derived from material-phase concentration profiles
Atmospheric Environment, In
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Xu, M. Rao and D. Enke
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Neural Networks, 13(4-5), 2000, 407-410
P. J. G. Lisboa, A. Vellido and H. Wong
2. Mining association rules procedure to support on-line recommendation by customers and products fragmentation. Expert Systems with Applications, 20(4), 2001, 325-335
S. Wesley Changchien and Tzu-Chuen Lu
3. The cluster-indexing method for case-based reasoning using self-organizing maps and learning vector quantization for bond rating cases
Expert Systems with
Applications,
21(3), 2001, 147-156
Kyung-Sup Kim and Ingoo Han
4. Applying AI technology and rough set theory for mining association rules to support crime management and fire-fighting resources allocation
Journal of Information, Technology and Society, 2002(2), 65-78
Show-Chin Lee, Mu-Jung Huang.
5. Distance matrix based clustering of the Self-Organizing Map
In José R. Dorronsoro, editor, Artificial Neural Networks - ICANN 2002, LNCS, 2415, 951-956, Madrid, Spain, 2002. Springer.
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6. Market segmentation via structured click stream analysis
Industrial Management & Data Systems, 102(9), 2002
Wen, Kuang-Wei; Peng, Kuo-Fang
7. Bibliography of Self-Organizing Map (SOM) Papers: 1998-2001 Addendum.
Neural Computing Surveys, 3, 2002, 1-156.
Merja Oja, Samuel Kaski and Teuvo Kohonen
8. An Automated Report Generation Tool for the Data Understanding Phase
In A. Abraham and M. Köppen (eds.) Hybrid Information Systems, Physica Verlag, Heidelberg, 611-626, 2002.
Juha Vesanto and Jaakko Hollmen
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In Jatinder N.D. Gupta, Kate A. Smith (Eds.), Neural Networks in Business, Chapter 1. Idea Group Inc. (2002)
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10. Evolution of Artificial Neural Networks in Business Applications: An Empirical Investigation Using a Growth Model
International Journal of Management & Decision Making, 3(1), 2002, 19-34.
Quaddus, M.A., and Khan, M.S.
11. Application of data mining to customer relationship management - The case of cosmetics
Journal of the Chinese Institute of Industrial Engineers, 19 (6), 2002, pp.45-59.
Chang, P.-C., Tsai, J.-Y., Hsieh, J.-C.
12. Forecast model for stock market based on artificial neural networks
Journal of Jilin University (Information Science Edition), 2002, 20(4), 68-70.
孙丹 张秀艳
13. Classification of consumers’ perceived risk: sources versus consequences
In Proc. of the 6th Pacific Asian Conference on Information Systems (PACIS 2002), 2002, 540-554
Nena Lim
14. The collaborative filtering recommendation based on SOM cluster-indexing CBR
Expert Systems with Applications, 25(3), 2003, 413-423
Tae Hyup Roh, Kyong Joo Oh and Ingoo Han
15. Consumers’ perceived risk: sources versus consequences
Electronic Commerce Research and Applications, 2(3), 2003, 216-228
Nena Lim
16. The Use of a Bayesian Confidence Propagation Neural Network in Pharmacovigilance
PhD Thesis. Umea University, Sweden (2003)
Andrew Bate
17. Applying AI technology and rough set theory to mine association rules for supporting knowledge management
In Proc. of the International Conference on Machine Learning and Cybernetics (ICMLC), 2003, 1820- 1825 Vol.3.
Zhe Huang and Yun-Quan Hu
18. Economic and Competitive Environment Analysis in the Formulation of Strategy: A Decision-Oriented Study Utilizing Self-Organizing Maps
PhD Thesis, Turku School of Economics and Business Administration. Finland (2004)
Aapo Länsiluoto
19. Internet market segmentation – an exploratory study of critical success factors
Marketing Intelligence & Planning, 2004, 22(6) 601-622
Tom M.Y. Lin, Pin Luarn and Peter K.Y. Lo
20. Unsupervised MRI tissue classification by support vector machines
Proceedings of the IASTED International Conference on Biomedical Engineering, 2004, 88-91.
Karp, E., Vigário, R.
21. Independent component analysis decomposition of structural MRI
Proceedings of the IASTED International Conference on Biomedical Engineering, 2004, 83-87.
Karp, E., Gävert, H., Särelä, J., Vigário, R.
22. Customer Segmentation based on Model of Multiple Classifiers Syncretizing
Management Sciences in China, 2004, 17(2), 64-67.
叶强 邹鹏 尚维
23. Segmenting Internet shoppers based on their Web-usage-related lifestyle: a cross-cultural validation
Journal of Business Research, 58(1), 79-88, (2005)
Malaika Brengman, Maggie Geuens, Bert Weijters, Scott M. Smith and William R. Swinyard
24. Market Basket Analysis by Means of a Growing Neural Network
The International Review of Retail, Distribution and Consumer Research, 15(2), 2005, 151-169.
Decker, R.
25. Extracting salient dimensions for automatic SOM labelling
IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 35(4), 2005, 595-600.
Azcarraga, A.P., Hsieh, M.-H., Pan, S.L., Setiono, R.
26. Using a clustering genetic algorithm to support customer segmentation for personalized recommender systems
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) LNAI 3397, 409-415.
Kim, K.-J., Ahn, H.
27. Logistics enterprise classifying model
Journal of Traffic and Transportation Engineering, 5 (2), 2005, 117-121.
Mao, H.-J., Zhang, Y., Li, X.-H.
28. Computer assisted customer churn management: State-of-the-art and future trends
Computers & Operations Research, In Press (2006)
John Hadden, Ashutosh Tiwari, Rajkumar Roy and Dymitr Ruta
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based on hierarchical self-organizing map
for markets of multimedia on demand
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Applications, In
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31. Knowledge discovery in
financial investment for forecasting
and trading strategy through wavelet-based SOM networks
Expert Systems
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Sheng-Tun Li and Shu-Ching Kuo
32. Searching customer
patterns of mobile service using clustering
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Yoonseong Kim
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IEE Colloquium (Digest) 514, pp. 5/1-5/5.
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The calculation of
sensitometric properties of 1,2,4-triazolo[1,5-a]pyrimidines by use of
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H. J. van Staveren, R. L. P. van Veen, O. C. Speelman, M. J. H. Witjes,
W. M. Star and J. L. N. Roodenburg
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Proceedings of MEDSIP, Bristol, 88-95, 2000. Keynote address.
Lee, Y.Y.B., Huang, Y., El-Deredy, W., Lisboa, P.J.G. and Harris, P.
5. Nonhistological Diagnosis of Human Cerebral Tumors by 1H Magnetic Resonance Spectroscopy and Amino Acid Analysis
Clinical Cancer Research, 6, 2000, 3983-3993
J.M. Roda, J.M. Pascual, F. Carceller, F. González-Llanos, A. Pérez-Higueras, J. Solivera, L. Barrios and S. Cerdán
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Pattern recognition methods
and applications in biomedical magnetic resonance
Progress in
Nuclear Magnetic Resonance Spectroscopy, 39(1), 2001, 1-40
J. C. Lindon, E. Holmes and J. K. Nicholson
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Automated Mode-of-Action
Detection by Metabolic Profiling
Biochemical
and Biophysical Research Communications, 286(1), 2001, 150-155
Nelly Aranìbar, Bijay K. Singh, Gerald W. Stockton and Karl-Heinz Ott
8. Data mining of spectroscopic data for biomarker discovery
Current Opinion in Drug Discovery and Development 4 (3), 2001, 325-331.
Norton, S.M., Huyn, P., Hastings, C.A., Heller, J.C.
9. Metabonomics classifies pathways affected by bioactive compounds. Artificial neural network classification of NMR spectra of plant extracts
Phytochemistry, 62(6), 2003, 971-985
Karl-Heinz Ott, Nelly Araníbar, Bijay Singh and Gerald W. Stockton
10. [SELF-CITATION] Tumour grading from magnetic resonance spectroscopy: a comparison of feature extraction with variable selection
Statistics in Medicine 22(1), 2003, 147-164
Y. Huang, P.J.G. Lisboa , W. El-Deredy
11. Visualizing metabolic changes in breast-cancer tissue using 1H-NMR spectroscopy and Self-Organizing Maps
NMR in Biomedicine, 16(1), 2003, 1-11
Olaf Beckonert, Jürgen Monnerjahn, Ulrich Bonk, and Dieter Leibfritz
12. Proton MR CSF analysis and a new software as predictors for the differentiation of meningitis in children
NMR in Biomedicine, 18(4), 2005, 213-225
Arunachalam Subramanian, Abhishek Gupta, Swapnil Saxena, Ashish Gupta, Raj Kumar, Anjali Nigam, Rashmi Kumar, Sudhir K. Mandal, and Raja Roy
13. A robust clustering approach for NMR spectra of natural product extracts
Magnetic Resonance in Chemistry, 43, 2005, 359-365
G.K. Pierens, M.E. Palframan, C.J. Tranter, A.R. Carroll and R.J. Quinn
14. Optimal classification of long echo time in vivo magnetic resonance spectra in the detection of recurrent brain tumors
NMR in Biomedicine, 2006, in press
B.H. Menze, M.P. Lichy, P. Bachert, B.M. Kelm, H.-P. Schlemmer, F.A. Hamprecht
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IEEE Transactions on Neural Networks, 17(2), 2006, 471-481.
Cawley, G.C., Talbot, N.L.C., Janacek, G.J., Peck, M.W.
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1. Applications of artificial neural network in AIDS research and therapy
Current Pharmaceutical Design, 8(8), 2002, 659-670.
Sardari, S., Sardari, D.
2. Metabonomics classifies pathways affected by bioactive compounds. Artificial neural network classification of NMR spectra of plant extracts
Phytochemistry, 62(6), 2003, 971-985
Karl-Heinz Ott, Nelly Araníbar, Bijay Singh and Gerald W. Stockton
3. A robust clustering approach for NMR spectra of natural product extracts
Magnetic Resonance in Chemistry, 43, 2005, 359-365
G.K. Pierens, M.E. Palframan, C.J. Tranter, A.R. Carroll and R.J. Quinn
Last updated 28/11/06