 | 2011 |
|---|
| 10 |       | Lourdes Cecilia Sáiz Bárcena,
Arturo Pérez,
Álvaro Herrero,
Emilio Corchado:
Analyzing Key Factors of Human Resources Management.
IDEAL 2011: 463-473 |
| 2010 |
|---|
| 9 | | Emilio S. Corchado,
Aitor Mata,
Álvaro Herrero,
Lourdes Sáiz Bárcena:
On the improvement of Knowledge Management status through case-based reasoning in a hybrid approach.
HIS 2010: 67-72 |
| 8 | | Álvaro Herrero,
Lourdes Cecilia Sáiz Bárcena,
Emilio Corchado:
Assessing Knowledge Management in the Power Sector through a Connectionist Model.
PAAMS (Special Sessions and Workshops) 2010: 721-729 |
| 7 | | Álvaro Herrero,
Emilio Corchado,
Lourdes Sáiz Bárcena,
Ajith Abraham:
DIPKIP: A Connectionist Knowledge Management System to Identify Knowledge Deficits in Practical Cases.
Computational Intelligence 26(1): 26-56 (2010) |
| 2009 |
|---|
| 6 | | Álvaro Herrero,
Aitor Mata,
Emilio Corchado,
Lourdes Sáiz Bárcena:
A Hybrid Solution for Advice in the Knowledge Management Field.
HAIS 2009: 157-168 |
| 2008 |
|---|
| 5 | | Ana María Lara Palma,
Lourdes Sáiz Bárcena,
Joaquín A. Pacheco,
Rafael Brotóns:
Optimization of Knowledge in Companies Simulating M6PROK© Model Using as Hybrid Methodology a Neuronal Network and a Memetic Algorithm.
HAIS 2008: 188-195 |
| 2006 |
|---|
| 4 | | Ana María Lara Palma,
Lourdes Cecilia Sáiz Bárcena,
Joaquín A. Pacheco:
A Closed Model for Measuring Intangible Assets: A New Dimension of Profitability Applying Neural Networks.
IDEAL 2006: 815-822 |
| 2004 |
|---|
| 3 | | Emilio Corchado,
Juan M. Corchado,
Lourdes Sáiz Bárcena,
Ana María Lara Palma:
Constructing a Global and Integral Model of Business Management Using a CBR System.
CDVE 2004: 141-147 |
| 2 | | Emilio Corchado,
Colin Fyfe,
Lourdes Sáiz Bárcena,
Ana María Lara Palma:
Development of a Global and Integral Model of Business Management Using an Unsupervised Model.
IDEAL 2004: 499-504 |
| 1 | | Emilio Corchado,
Juan M. Corchado,
Lourdes Sáiz Bárcena,
Ana María Lara Palma:
A Beta-Cooperative CBR System for Constructing a Business Management Model.
Industrial Conference on Data Mining 2004: 42-49 |
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