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P. Delatorre, León, C., Salguero, A., and Mateo-Gil, C., The Long Path of Frustration: a case of study with Dead by Daylight, in I. Rojas et al. (eds.): Advances in Computational Intelligence, 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, Cádiz, Spain, June 14-16, Proceedings, Part II, LNCS 10306, 2017.PDF icon Delatorre 2017 - Long path of frustration.pdf (343.72 KB)
P. Gervás, Concepción, E., León, C., Méndez, G., and Delatorre, P., The Long Path to Narrative Generation, IBM Journal of Research & Development, vol. 63, pp. 1-8, 2019.PDF icon Gervasetal2019LongPathNarrativeGeneration.pdf (596.84 KB)
F. Peinado, Los videojuegos y sus fronteras. Desafíos de producción y diseño para las nuevas generaciones, in Tempo 2009, Albacete, España, 2009.
M
S. Bautista and Saggion, H., Making Numerical Information more Accessible: Implementation of a Numerical Expressions Simplification Component for Spanish, ITL- International Journal of Applied Linguistics, pp. 299-323, 2014.PDF icon Bautista_Saggion_CR_ITL_SIRS.pdf (455.47 KB)
M. Ballesteros and Nivre, J., MaltOptimizer: A System for MaltParser Optimization, in The 8th international conference on Language Resources and Evaluation (LREC 2012), Istanbul, 2012.PDF icon MaltOpt.pdf (156.64 KB)
M. Ballesteros and Nivre, J., MaltOptimizer: An Optimization Tool for MaltParser, in 13th Conference of the European Chapter of the Association for computational Linguistics (EACL 2012). Demo Session, Avignon, 2012.PDF icon eacl2012.pdf (148.49 KB)
A. Aggarwal, Gervás, P., and Hervás, R., Measuring the Influence of Errors Induced by the Presence of Dialogues in Reference Clustering of Narrative Text, 7th International Conference on Natural Language Processing (ICON 09). Hyderabad, India, pp. 209-218, 2009.PDF icon AggarwalICON09.pdf (216.84 KB)
A. J. Jimeno-Yepes, Plaza, L., Mork, J. G., Aronson, A., and Díaz, A., MeSH indexing based on automatically generated summaries, BMC bioinformatics, vol. 14, 2013.
P. Gervás, Metrics for Desired Structural Features for Narrative Renderings of Game Logs, Journal of Entertainment Computing, 2014.
E. Concepción, Gervás, P., and Méndez, G., A microservice-based architecture for story generation, in Microservices, Odense, Denmark, 2017.PDF icon ConcepcionEtAl-Microservices2017.pdf (150.21 KB)
P. Gervás, de Antonio, A., and Amores, G., MILES (Modelos de Interacción centrados en Lenguaje, Espacio y Semántica computacional), in Congreso de la Sociedad Española para el Procesamiento del Lenguaje Natural (SEPLN 2012), Castellón, Spain, 2012.PDF icon milesARTsepln CRC.pdf (145.78 KB)
E. Concepción, Gervás, P., and Méndez, G., Mining Knowledge in Storytelling Systems for Narrative Generation, in CC-NLG: Computational Creativity in Natural Language Generation (@INLG2016), Edimburgh, UK, 2016.PDF icon Concepcionetal-CC-NLG.pdf (151.21 KB)
F. Peinado and Gervás, P., Minstrel Reloaded: From the Magic of Lisp to the Formal Semantics of OWL, in 3rd International Conference on Technologies for Interactive Digital Storytelling and Entertainment (TIDSE), Darmstadt, Germany, 2006, vol. 4326, pp. 93-97.PDF icon 2006-peinado-minstrel.pdf (84.98 KB)
P. Pérez, Méndez, G., and de Antonio, A., mIVA: Why to use Mobile Agents in Virtual Environments and Wireless Devices?, in 15th European Conference on Artificial Intelligence (ECAI2002). Workshop 6: Artificial Intelligence in Mobile Systems, 2002.PDF icon AIMS2002.pdf (439.01 KB)
C. León, Hassan, S., Gervás, P., and Pavón, J., Mixed Narrative and Dialog Content Planning Based on BDI Agents, in XII Conferencia de la Asociación Española para Inteligencia Artificial, Salamanca, Spain, 2007.PDF icon caepia07.pdf (148.32 KB)
D. Dionne, de la Puente, S., León, C., Hervás, R., and Gervás, P., A Model for Human Readable Instruction Generation Using Level-Based Discourse Planning and Dynamic Inference of Attributes Disambiguation, in 12th European Workshop on Natural Language Generation, Athens, Greece, 2009.PDF icon nlgenvironment.pdf (1.89 MB)
G. Méndez, Gervás, P., and León, C., A Model of Character Affinity for Agent-Based Story Generation, in 9th International Conference on Knowledge, Information and Creativity Support Systems, Limassol, Cyprus, 2014.PDF icon MendezGervasLeon-kicss2014.pdf (345.73 KB)
M. Wilder and Gervás, P., A Model of Character Evolution based on Stanislavsky-driven BDI Agents, in 6th International Workshop on Computational Creativity, Concept Invention, and General Intelligence, Madrid, Spain, 2017.PDF icon C3GI_2017_paper_12.pdf (389.34 KB)
P. Gervás, A Model of Interpretation of Embedded Stories, in Text2Story: 4th International Workshop on Narrative Extraction from Texts, Lucca, Tuscany, 2021.PDF icon Text2Story2021-paper11-rev.pdf (234.02 KB)
P. Gervás, Modelado automático de procesos creativos: ¿hasta dónde se puede llegar?, in El arte de educar creativamente. Reflexiones para una educación artística contemporánea., P. Tudela Caño and García, P. Paraja Santa Cruz de Tenerife: TEA Tenerife Espacio Escénico de las Artes, 2019, p. 227--239.
A. Díaz and Gervás, P., Modelado dinámico de usuario en un sistema de personalización de contenidos Web, CAEPIA-TTIA 2003 , vol. Volumen II. pp. 45-54, 2003.PDF icon Diaz&Gervas 2003 (CAEPIA).pdf (207.12 KB)
P. Gervás, Modeling Literary Style for Semi-automatic Generation of Poetry, in User Modeling 2001, 8th International Conference, Sonthofen, Germany, 2001, pp. 231-233.
N. Alvarez-Ayerza and Peinado, F., Modelling Suspicion as a Game Mechanism for Designing a Computer-Played Investigation Character, in Congreso de la Sociedad Española Para las Ciencias del Videojuego, Barcelona, España, 2015.
P. Gervás and Murciano, R., Modelling the Generation of Customised Poetry in JESS, in Proceedings of the Third International Conference on Enterprise Information Systems, 2001, pp. 543-552.
M. Miranda and Peinado, F., Modelos De Comportamiento De Unidades Militares De Un Videojuego De Estrategia En Tiempo Real Basados En Máquinas De Estado Multinivel, in Congreso Internacional de Arte, Diseño y Desarrollo de Videojuegos en la Industria Creativa, Madrid, España, 2015.

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