Publications

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  • Journal Articles:
    • A. Bogarin, R. Cerezo, C. Romero. A survey on educational process mining. WIREs Data Mining Knowledge Discovery 2018, In Press.
    • C. Romero, S. Ventura. Educational data science in massive open online courses. WIREs Data Mining Knowledge Discovery 2017, 7(1), 1-12.
    • J. M. Luna, C. Castro, C. Romero. MDM Tool: A Data Mining Framework Integrated Into Moodle. Computer Applications in Engineering Education. 2017, 25(1), 90-102.
    • C. Marquez, C.Romero, A.Cano. S.Ventura. Early Dropout Prediction using Data Mining: A Case Study with High School Students. Expert Systems. 2016. 33(1): 107-124.
    • J.L. Olmo, C.Romero, E.Gibaja, S.Ventura. Improving Meta-learning for Algorithm Selection by Using Multi-label Classification: A Case of Study with Educational Data Sets. International Journal of Computational Intelligence Systems. 8(6):1144-1164, 2015
    • Peter Brusilovsky, Mike Sharples, Gustavo R. Alves, Tiffany Barnes, Sherry Y. Chen, Carol. H. C. Chu, Hendrik Drachsler, Seiji Isotani, Euan Lindsay, Xavier Ochoa, Mykola Pechenizkiy, Ma. Mercedes T. Rodrigo, Cristóbal Romero, Sergey A. Sosnovsky, Stefaan Ternier, Katrien Verbert: Editorial: A Message from the Editorial Team and an Introduction to the January-March 2016 Issue. TLT 9(1): 1-4
    • C. Romero. S. Ventura 2015. Larusson, J.A., White, B. (eds): Learning Analytics: From Research to Practice. Technology, Knowledge and Learning. 20:357-360, 2015.
    • A. Zapata, V. H. Menéndez, M.E. Prieto, C. Romero. Evaluation and Selection of Group Recommendation Strategies for Collaborative Searching of Learning Objects. International Journal of Human-Computer Studies. 76:22-39, 2015.
    • T.Y. Tang, B.K. Daniel, C. Romero. Recommender systems for and in social and online learning environments. Expert Systems. 32(2):261-263, 2015.
    • J.M. Luna, , J.R. Romero, C. Romero, S. Ventura. An Evolutionary Algorithm for the Discovery of Rare Class Association Rules in Learning Management Systems. Applied Intelligence. 42:501-513, 2015.
    • J.M. Luna, , J.R. Romero, C. Romero, S. Ventura. Mining Optimized Quantitative Association Rules by using a Genetic Programming Free-parameter Algorithm. Integrated Computer-Aided Engineering. 21:321-337, 2014.
    • J.M. Luna, , J.R. Romero, C. Romero, S. Ventura. On the Use of Genetic Programming for Mining Comprehensible Rules in Subgroup Discovery. IEEE TRANSACTIONS ON CYBERNETICS. 44(12):2329-2341, 2014.
    • J.M. Luna, , J.R. Romero, C. Romero, S. Ventura. Reducing gaps in quantitative association rules: A genetic programming free-parameter algorithm. Integrated Computer-Aided Engineering. 21: 321-337, 2014.
    • C. Romero, R. Baker. A Review of Classroom Assessment in Action. American Journal of Psychology, 127(1), 134-136. 2014.
    • S. Ventura, C. Romero, A. Abraham. Foreword: Intelligent data analysis, Journal of Computer and System Sciences, Num. 80:1–2. 2014.
    • C. Romero, M.I. Lopez, J.M. Luna, S. Ventura, Predicting students' final performance from participation in online discussion forums. Computers&Education. Num. 68: 458–472, 2013.
    • J.C. Krzysztof, C. Romero, J.M. Benitez, F. Marcelloni. Introduction. Integrated Computer-Aided Engineering. Vol. 20(3):199-199, 2013.
    • C.Romero, A. Zafra, J.M. Luna, S. Ventura. Association rule mining using genetic programming to provide feedback to instructors from multiple-choice quiz data. Expert Systems: The Journal of Knowledge Engineering. Vol.30(2): 162–172, 2013.
    • A. Zafra, C. Romero, S. Ventura. DRAL: A Tool for Discovering Relevant e-Activities for Learners. Knowledge and Information Systems (KAIS). Vol. 36:211–250. 2013.
    • C. Marquez-Vera, A. Cano, C. Romero, S. Ventura. Predicting student failure at school using genetic programming and different data mining approaches with high dimensional and imbalanced data. Applied Intelligent. Vol. Vol. 38(3):315-330. 2013.
    • C. Marquez-Vera, C. Romero, S. Ventura. Predicting School Failure and Dropout by Using Data Mining Techniques. IEEE Rita. Vol. 7(3):109-117. 2013.
    • C. Romero, P.G. Espejo, A. Zafra, J.R. Romero, S. Ventura. Web Usage Mining for Predicting Final Marks of Students that Use Moodle Courses. Computer Applications in Engineering Education journal. Vol. 21:135-146, 2013
    • A. Zapata , V. H. Menéndez, M.E. Prieto, C. Romero. A Framework for Recommendation in Learning Object Repositories: An Example of Application in Civil Engineering. Advances in Engineering Software. Vol. 56, 1-14, 2013
    • C.Romero, S. Ventura. Data Mining in Education. WIREs Data Mining and Knowledge Discovery. John Wiley & Sons. Vol. 3:12-27. 2013.
    • C. Romero. S. Ventura. Preface to the Special Issue on Data Mining for Personalised Educational Systems. User Modeling and User-Adapted Interaction. Springer. Vol.21, Num. 1-2, Pp. 1-3, 2011.
    • C. Romero, J.M. Luna, J.R. Romero, S. Ventura. RM-Tool: A framework for discovering and evaluating association rules. Advances in Engineering Software. Vol 42. Pp. 566-576, 2011.
    • A. Zapata, V.H. Menendez, M. E. Prieto, C. Romero. A Hybric Recommender Method for Learning Objects. International Journal of Computer Applications. Number 1. Pp. 1-7. 2011.
    • A. Zafra, C. Romero, S. Ventura. Multiple Instance Learning for Classifying Students in Learning Management Systems. Expert Systems With Applications. Vol. 38. Pp. 15020-15031, 2011.
    • E. García, C. Romero, S. Ventura, C. de Castro. A collaborative educational association rule mining tool. Internet and Higher Education. Special Issue Web Mining and Higher Education, Vol 14. Issue 2, pp. 77–88, 2011.
    • C. Romero, S. Ventura. Educational Data Mining: A Review of the State-of-the-Art. IEEE Transaction on Systems, Man, and Cybernetics, Part C: Applications and Reviews. Issue 6, pp.601 - 618, 2010.
    • C. Romero, S. Ventura, A. Zafra, P. de Bra. Applying Web Usage Mining for Personalizing Hyperlinks in Web-based Adaptive Educational Systems. Computer&Education. Volume 53, Issue 3, Pages: 828-840. 2009.
    • A. Zafra, C. Romero, S. Ventura, E. Herrera-Viedma. Multi-Instance Genetic Programming For Web Index Recommendation. Expert Systems With Applications. Vol. 36. Pag. 11470-1147. 2009.
    • E. García, C. Romero, S. Ventura, C. de Castro.An architecture for making recommendations to courseware authors through association rule mining and collaborative filtering. User Modelling and User Adapted Interaction. Vol. 19. Num. 1-2. Pages: 99-132. 2009.
    • E. Garcia, C. Romero, S. Ventura, C. Castro. Sistema recomendador colaborativo usando minería de datos distribuida para la mejora continua de cursos e-learning. IEEE Rita: Revista Iberoamericana de Tecnologías del Aprendizaje. Vol. 3. Num 1. Mayo 2008. Pag. 19-30.
    • C. Romero, S. Ventura, P. de Bra. Using Mobile and Web-based computerized tests to evaluate university students. Computers Applications in Engineering Education. John Wiley & Sons. Volumen 17, Issue 4, pages 435-447. 2009.
    • J. Alcalá, L. Sánchez, S. García, M.J. del Jesus, S. Ventura, J.M. Garrell, J. Otero, C. Romero, J. Bacardit, V. Rivas and F. Herrera. KEEL: A data mining software tool for assessing the performance of knowledge extraction-based on evolutionary algorithms. Soft Computing, Vol 13. Pages: 307-318. 2009.
    • C. Romero, S. Ventura and E. García. Data Mining in Course Management Systems: MOODLE Case Study and Tutorial. Computers and Education, 2007. Num. 51. pp. 368-384.
    • S. Ventura, C. Romero, A. Zafra, J.A. Delgado and C. Hervás. JCLEC: A Java Framework for Evolutionary Computation. Soft Computing, 2007. 12 (4) pp. 381-392..
    • C. Romero and S. Ventura. Educational Data Mining: A Survey from 1995 to 2005. Expert Systems with Applications, 33(1), 135-146, 2007.
    • P.G. Espejo, C. Hervás, S. Ventura and C. Romero. Eleccion de Operadores Lógicos para la Inducción de Conocimiento Comprensible. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial, 29,19-30, 2006.
    • C. Romero, S. Ventura, E. Gibaja, C. Hervás and F. Romero. Web-Based Adaptive Training Simulator System for Cardiac Life Support. Artificial Intelligence in Medicine, 38(1), 67-78, 2006.
    • C. Romero, S. Ventura, C. Hervás and P. González. Rule Discovery in Web-Based Educational Systems Using Grammar-Based Genetic Programming. WIT Transactions on Information and Communication Tecnologies, 35, 205-214, 2005.
    • C. Romero, S. Ventura, C. de Castro and E. García. Algoritmos Evolutivos para el Descubrimiento de Reglas de Predicción en la Mejora de de Sistemas Educativos Basados en Web. RELATEC (Revista Latinoamericana De Tecnología Educativa), 2, 1-12, 2005.
    • C. Romero, S. Ventura and P. de Bra. Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors. User Modelling and User Adapted Interaction, 14(5), 425-464, 2004.
    • C. Romero, S. Ventura, C. de Castro and E. García. Herramienta Autor INDESAHC Para La Creación de Cursos Hipermedia Adaptativos. RELATEC (Revista Latinoamericana De Tecnología Educativa), 1, 349-367, 2004.
    • C. Romero, C. de Castro and S. Ventura. Construcción de Cursos Hipermedia Adaptativos Basados En Web Utilizandoa AHA. Revista Iberoamericana de Educación a Distancia, 5(2), 99-116, 2002.
  • Contributions to International Conferences:
    • P. González, E. Gibaja, A. Zapata, V. H. Menéndez, C. Romero. Towards Automatic Classification of Learning Objects: Reducing the Number of Used Features, EDM 2017. 1-2.
    • A. Zapata, V.H. Menéndez, C. Romero, M.E. Prieto. Meta-learning for predicting the best vote aggregation method: Case study in collaborative searching of Los. EDM 2016. 656-657.
    • C. Romero, R. Cerezo, J.A. Espino, M. Bermudez. Using Android Wear for Avoiding Procrastination Behaviours in MOOCs. L@S 2016. Edimburgo, 193-196.
    • Bogarin, A., Romero, C., Cerezo R. 2015. Discovering student's navigation path in moodle. International Conference on Educational Data Mining, Madrid, Spain, 556-557. 2015.
    • M.A. Jiménez-Cómez, J. M. Luna, C. Romero, S. Ventura. Discovering Clues to Avoid Middle Shool Failure as Early as Possible. Learning Analytics and Knowledge Conference, NY, USA. 300-305. 2015.
    • Fuentes, J., Romero, C., García-Martínez, C., Ventura. S. Accepting or Rejecting Students’ Self-grading in their Final Marks by using Data Mining. International Conference on Educational Data Mining, London, UK, 327-328. 2014.
    • Bogarin, A., Romero, C. Cerezo, R. Sanchez-Santillan, M. Clustering for improving Educational Process Mining. Learning Analytics and Knowledge Conference 2014. Indianapolis, USA, Pp. 11-15, 2014.
    • C.Romero, C.Castro, S.Ventura. A Moodle Block for Selecting, Visualizing and Mining Students' Usage Data. 6th International Conference on Educational Data Mining, Memphis, TN, USA, 400-401, 2013.
    • C. Romero, J.L. Olmo, S. Ventura. A meta-learning approach for recommending a subset of white-box classication algorithms for Moodle datasets. 6th International Conference on Educational Data Mining, Memphis, TN, USA, 268-271. 2013
    • J. M. Luna, J. R. Romero, C. Romero, and S. Ventura. Discovering Subgroups by Means of Genetic Programming. 16th European Conference on Genetic Programming, Vienna, Austria. pp. 121–132, 2013
    • Molina, M.M., Romero, C. Luna, J.M. Ventura. S. Meta-learning approach for automatic parameter tuning: A case study with educational datasets. 5th International Conference on Educational Data Mining, pp. 180-183, 2012.
    • Lopez, M.I., Luna, J.M., Romero, C., Ventura. S. Classification via clustering for predicting final marks starting from the student participation in forums. 5th International Conference on Educational Data Mining. pp. 148-151. 2012.
    • Luna, J.M., Romero, J.R., Romero, C. Ventura. S., A Genetic Programming Free-Parameter Algorithm for Mining Association Rules. Jose Maria Luna, Jose Raul Romero, Cristobal Romero, Sebastian Ventura. ISDA 2012. Chania, India. International Conference on Intelligent Systems Design and Applications. pp. 64-69, 2012.
    • V.H. Menendez-Dominguez, A. Zapata, M.E. Prieto-Mendez, C. Romero, J. Serrano-Guerrero. A similarity-based approach to enhance learning objects management systems. ISDA 2011 11th International Conference on Intelligent Systems Design and Applications. Pp- 996-1001, 2011.
    • C. Marquez-Vera, C. Romero, S. Ventura. Predicting School Failure Using Data Mining. International Conference on Educational Data Mining. Pag. 271-275, 2011.
    • R. Pedraza, C. Romero, S. Ventura. A Java desktop tool for mining Moodle data. International Conference on Educational Data Mining. Pag. 319-320, 2011.
    • A. Zapata, V.H. Menéndez-Dominguez, M. Prieto-Mendez, C. Romero. Using data mining in a recommender system to search for learning objects in repositories. International Conference on Educational Data Mining. Pag. 321-323, 2011.
    • C. Romero, S. Ventura, E. Vasilyeva, M. Pechenizkiy. Using Class Association Rules over Students’ Test Data. International Conference on Educational Data Mining. Pittsburgh, PA, USA. Pp. 317-318. 2010.
    • C. Romero, J.R Romero, J. M. Luna, S. Ventura. Mining Rare Association Rules from e-Learning Data. International Conference on Educational Data Mining. Pittsburgh, PA, USA. Pp. 171-180. 2010.
    • C.J. Carmona, P. González, M.J. del Jesus, S. Ventura, C. Romero. Evolutionary algorithms for subgroup discovery applied to e-learning data. IEEE EDUCON Education Engineering, Madrid. Page 1-7. 2010.
    • A. Zafra, C. Romero, S. Ventura. Predicting Academic Achievement Using Multiple Instance Genetic Programming. Workshop EDM en ISDA’09 IEEE Ninth International Conference on Intelligent Systems Design and Applications. Pisa. Italia. pp. 1120-1125. 2009.
    • C. Romero, S. Ventura, E. García, C. de Castro, M. Gea. Collaborative Data Mining Tool for Education. EDM’09. 1-3 Julio, Córdoba. Pag. 299-306. 2009.
    • E. García, C. Romero, S. Ventura, C. de Castro. Evaluating web based instructional model using association rule mining. UMAP 2009. 22-26 June. Trento, Italy. LNCS 5535. Pp. 16-29. 2009.
    • C. Romero, S. Ventura, P. Espejo, C. Hervas. Data mining algorithms to classify students. Educational Data Mining Conference EDM 2008. Montreal. Junio 20-21. Pag. 182-185.
    • S. Ventura, C. Romero, C. Hervás. Analyzing rule evaluation measures with educational datasets: A framwork to help the teacher. Educational Data Mining Conference EDM 2008. Montreal. Junio 20-21. Pag. 182-185.
    • C. Romero, S.Guiterrez, M. Freire, S. Ventura. Minig and visualizing trails in Web-based educational systems. Educational Data Mining Conference EDM 2008. Montreal. Junio 20-21. Pag. 182-185.
    • A. Zafra, S. Ventura, E. Herrera-Viedma and C. Romero. Multiple Instance Learning with Genetic Programming For Web Mining. 9th International Work-Conference on Artificial Neural Networks (IWANN 2007). S. Sebastian (Spain), 2007.
    • E. García, C. Romero, S. Ventura y T. Calders. Drawbacks and solutions of applying association rule mining in learning management systems. International Workshop on Applying Data Mining in e-learning (ADML'07). Crete (Greece), 2007.
    • C. Romero, S. Ventura, J.A. Delgado and P. de Bra. Personalized Links Recommendation Based On Data Mining in Adaptive Educational Hypermedia Systems. Second European Conference on Technology Enhanced Learning (EC-TEL 2007). Crete (Greece), 2007.
    • E. García, C. Romero, S. Ventura, and C. de Castro. Using Rules Discovery For The Continuous Improvement of e-learning Courses. Seventh International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2006). Burgos (Spain), 2006.
    • C. Romero, S. Ventura and C. Hervás. Sistema Adaptable para la ejecución de Tests Informatizados en Teléfonos Móviles. II Congreso Iberoamericano sobre Computacióm Ubícua (CICU 2006). Madrid (Spain), 2006.
    • C. Romero, S. Ventura and C. Hervás. AHA! Meets SCORM. IADIS International Conference. Applied Computing 2005. Algarve (Portugal), 2005.
    • P. González, C. Romero, S. Ventura and C. Hervás. Induction of Classification Rules with Grammar-Based Genetic Programming. Second International Conference on Machine Intelligence (ACIDCA-ICMI 2005). Tozeur (Tunis), 2005.
    • C. Romero, S. Ventura, C. Hervás and P. de Bra. Extending AHA!: Adding Levels, Data Mining, Tests and SCORM to AHA!. Fifth International Conference Human Systems Learning. Marrakesh (Morocco), 2005.
    • C. Romero, P. de Bra, S. Palomo and S. Ventura. An Authoring Tool for Web-Based Adaptive and Classic Tests. AACE ELEARN'2004 conference. Washington DC (USA), 2004.
    • C. Romero, S. Ventura and C. de Castro. Herramienta para el Descubrimiento de Reglas de Predicción en Educación Basada en Web. V Congreso Internacional De Interacción Persona Ordenador. Lleida (Spain), 2004.
    • C. Romero, S. Ventura and C. de Castro. Sistema de Desarrollo Integrado para Cursos Hipermedia Adaptativos (INDESHAHC). V Congreso Internacional De Interacción Persona Ordenador. Lleida (Spain), 2004.
    • C. Romero, S. Ventura, C. Hervás and P. González. Rule Discovery in Web-Based Educational Systems using Grammar-Based Genetic Programming. Fifth International Conference On Data Mining. Málaga (Spain), 2004.
    • C. Romero, S. Ventura, C. de Castro and P. de Bra. Discovering Prediction Rules In AHA Courses!. User Modeling 2003. Pittsburg (USA), 2003.
    • C. Romero, S. Ventura and C. de Castro. Herramienta Autor para la Construcción de Cursos Hipermedia Adaptativos Utilizando AHA. IV Congreso Internacional de Interacción Persona-Ordenador. Vigo (Spain), 2002.
    • C. Romero, S. Ventura, C. de Castro and P. de Bra. Using Knowledge Levels with AHA for Discovering Interesting Relationships. World Conference E-Learn 2002. Toronto (Canada), 2002.
    • C. Romero, S. Ventura and C. de Castro. Using Genetic Algorithms for Data Mining in Web-Based Educational Hypermedia Systems. Adaptive Hypermedia and Adaptive Web-Based Systems (AH02). Málaga (Spain), 2002.
    • C. Romero, F. Vazquez, S. Ventura and C. de Castro. Internet Based Control Systems. Internet Based Control Systems. Madrid (Spain), 2002.
  • Books chapters:
    • C.Romero, R.Cerezo, A.Bogarín, M.Sánchez-Santillán. Educational Process Mining: A tutorial and case study using Moodle data sets Handbook of Data Mining and Learning Analytics. Wiley Series on Methods and Applications in Data Mining. Editors: S. ElAtia, O.R. Zaiane, Wiley, 2016, Pag. 3-28.
    • C.Romero. Foreward. Big Data and Learning Analytics: Current Theory and Practice in Higher Education. Editor: Ben Daniel. Springer. 2016, 7-8.
    • C.Romero, J.R. Romero, S.Ventura. A Survey on Pre-processing Educational Data. Educational Data Mining: Applications and Trends, Springer Series Studies in Computational Intelligence. Editor: Alejandro Peña-Ayala. Volume 524, pp 29-64, 2014
    • A. Zafra, C. Romero. S. Ventura. Classify students with Multiple-Instance Learning. Handbook of Educational Data Mining. Chapman and Hall/CRC Press, Taylor & Francis Group. Pages 187-200. 2010.
    • E. Garcia, C. Romero, S. Ventura, C. de Castro, T. Calders. Association Rule Mining in Learning Management Systems: Moodle. Handbook of Educational Data Mining. Chapman and Hall/CRC Press, Taylor & Francis Group. Pages 93-106. 2010.
    • C. Romero, S. Ventura, M. Pechenizkiy, R. Baker. Introduction. Handbook of Educational Data Mining. Chapman and Hall/CRC Press, Taylor & Francis Group. Pages. 1-8. 2010.
    • P. de Bra, N. Stash, D. Smits, C. Romero and S. Ventura. Authoring and Management Tools for Adaptive Educational Hypermedia Systems: The AHA! case study. En Evolution of Teaching and Learning Paradigms in Intelligent Environments, pp. 285-308. Springer, 2008.
    • C. Romero, S. Ventura, C. Hervás and P. González. Rule Discovery in Web-Based Educational Systems Using Grammar Based Genetic Programming. En Data Mining, Text Mining and Their Business Applications, pp 113-126. WIT Press, Essex (UK), 2005.
    • C. Romero, S. Ventura and C. Hervás. Descubrimiento de reglas de predicción en sistemas de e-learning usando Programación Genética. En R. Giráldez, J.C. Riquelme y J.S. Aguilar (Eds). Tendencias de la Minería de Datos en España. Red Española de Minería de Datos (TIC2002-11124-E), 2004.
    • C. Romero, S. Ventura and C. Hervás. Selección de medidas de evaluación de reglas obtenidas mediante Programación Genética Basada en Gramáticas. En R. Giráldez, J.C. Riquelme y J.S. Aguilar (Eds). Tendencias de la Minería de Datos en España. Red Española de Minería de Datos (TIC2002-11124-E), 2004.
  • Books:
    • Handbook of Educational Data Mining. C.Romero, S. Ventura, M. Pechenizky, R. Baker. Editorial Chapman and Hall/CRC Press, Taylor & Francis Group. Data Mining and Knowledge Discovery Series. ISBN 9781439804575, 2010.
    • Data Mining in e-learning. C. Romero y S. Ventura (eds.). Data Mining in e-learning. Advances in Management Information, Vol. 4. WIT Press. Wessex (UK), 2006. ISBN: 1-84564-152-3.
    • Programación en Lenguaje CLIPS.Editorial Ramón Areces. C. Romero, A. Calvo, P. Gonzalez, S. Ventura. ISBN: 84-8004-726-7. Pag. 294. 2005.
    • Domótica e Inmótica: Viviendas y Edificios Inteligentes. C. Romero, F. Vázquez, C. de Castro. Editorial Ra-ma. ISBN:84-7897-653-1. 2005. pag. 400.
    • Curso práctico para la obtención de la acreditación europea del manejo del ordenador. Editorial ANAYA-Multimedia. ISBN:84-415-1907-2. C. Romero, C. de Catro, S. Ventura, E. Garcia.  Page. 527. 2005.
    • Curso Básico de Java 1.2. C. Romero, C. de Castro, E. Lopez. Editorial: Publications Servirces Cordoba University and CajaSur. ISBN: 84-7801-591-4 2002
    • Curso Práctico de Unix. C. Romero, J. L. Cruz, S. Ventura. ISBN: 84-7959-300-8. Editorial: Publications Servirces Cordoba University and CajaSur. 1999.
    • Curso Práctico de Fortran 90. C. Romero, J. L. Cruz, S. Ventura. ISBN: 84-7959-338-5. Editorial: Publications Servirces Cordoba University and CajaSur. 2000.
    • Simulando con ACSL. C. Romero, F. Vazquez, C. de Castro. Editorial: Martínez Bernia y Asociados. Legal deposit: CO-311-2000. 2000.