Professorat i Investigació
Directori
Nin Guerrero, Jordi
Formació acadèmica
- Doctor en Ciències de la Computació.
- Ingeniero en informática.
- Ingenieria técnica en informática de gestión.
Biografia
És professor associat del Departament d'Operacions, Innovació i Ciències de les Dades d'Esade Universitat Ramon Llull.
Va obtenir el seu títol d'Informàtica el 2004 per la Universitat Autònoma de Barcelona UAB. Posteriorment, es va afiliar a l'Institut de Recerca d'Intel·ligència Artificial del Consell Nacional de Recerca IIIA-CSIC. El 2008, va aconseguir el seu Ph.D. en Informàtica, sent honorat amb el premi de doctorat excepcional pel departament d'informàtica de la UAB. Després d'això, va assumir un paper postdoctoral al Centre Nacional francès per a la Recerca Científica CNRS. El 2010 va assumir un càrrec de professor lector dins del Departament d'Arquitectura Informàtica de la Universitat Politècnica de Catalunya UPC. Demostrant una carrera versàtil, també va exercir com a científic de dades sènior a BBVA Data & Analytics de 2015 a 2019.
Des de 2019, ha reprès el seu viatge acadèmic com a professor associat a l'Escola de Negocis Esade Universitat Ramon Llull.
Les seves activitats acadèmiques giren al voltant de l'anàlisi de xarxes i l'aprenentatge automàtic, reflectint els seus interessos de recerca en ciència de dades i intel·ligència artificial.
Publicacions destacades
- Nin Guerrero, J., Salbanya Rovira, B. & Unceta Mendieta, I. (2023, October). Resource allocation in home care services using reinforcement learning [Paper presentation]. 25è Congrés Català d'Intel·ligència Artificial CCIA 202325, Sant Fruitós de Bages.
- Tous, R., Nin Guerrero, J. & Igual, L. (E-pub ahead of print). (2023). Human pose completion in partial body camera shots. Journal of Experimental and Theoretical Artificial Intelligence. DOI: https://doi.org/10.1080/0952813X.2023.2241575.
- Statuto, N., Unceta Mendieta, I., Nin Guerrero, J. & Pujol Vila, O. (Accepted/In press). (2023). A Scalable and Efficient Iterative Method for Copying Machine Learning Classifiers. Journal of Machine Learning Research, 24. DOI: https://doi.org/10.48550/arXiv.2302.02667.
- Unceta Mendieta, I. & Nin Guerrero, J. (2022, January). Copying Machine Learning Classifiers [Paper presentation]. International Conference on AI and Financial Services, Madrid.
- Unceta Mendieta, I., Salbanya Rovira, B. & Nin Guerrero, J. (2021). On the Convergence of Financial Distress Propagation on Generic Networks. In Villaret, M., Alsinet, T. & Fernandez, C., Valls, A. (Eds.), Artificial Intelligence Research and Development - Proceedings of the 23rd International Conference of the Catalan Association for Artificial Intelligence, CCIA 2021 (pp. 167-176). IOS Press BV. DOI: https://doi.org/10.3233/FAIA210130.
- Nin Guerrero, J., Salbanya Rovira, B., Fleurquin, P., Tomás, E., Arenas, A. & Ramasco, J. J. (2021). Modeling financial distress propagation on customer-supplier networks. Chaos, 31 (5), 053119. DOI: https://doi.org/10.1063/5.0041104.
- Nin Guerrero, J., Pujol Vila, O. & Unceta Mendieta, I. (2021). Differential replication for credit scoring in regulated environments. Entropy, 23, pp. 407-424. DOI: https://doi.org/10.3390/e23040407.
- Mougan, C., Masip, D., Nin Guerrero, J. & Pujol, O. (2021). Quantile Encoder. In Torra, V., Narukawa, Y. (Ed.), Modeling Decisions for Artificial Intelligence - 18th International Conference, MDAI 2021, Proceedings (pp. 168-180). Springer Science and Business Media Deutschland GmbH. DOI: https://doi.org/10.1007/978-3-030-85529-1_14.
- Unceta Mendieta, I., Nin Guerrero, J. & Pujol, O. (2021). Differential replication for credit scoring in regulated environments. Entropy, 23 (4), 407. DOI: https://doi.org/10.3390/e23040407.
- Unceta Mendieta, I., Nin Guerrero, J. & Pujol, O. (2020). Risk mitigation in algorithmic accountability: The role of machine learning copies. PLOS ONE, 15 (11 November), e0241286. DOI: https://doi.org/10.1371/journal.pone.0241286.
- Unceta Mendieta, I., Nin Guerrero, J. & Pujol, O. (2020). Environmental adaptation and differential replication in machine learning. Entropy, 22 (10), pp. 1-14. DOI: https://doi.org/10.3390/e22101122.
- Torra, V., Narukawa, Y., Nin Guerrero, J. & Agell Jané, N. (2020). Preface. Lecture Notes in Computer Science including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 12256 LNAI, pp. v.
- Unceta Mendieta, I., Nin Guerrero, J. & Pujol, O. (2020). Copying Machine Learning Classifiers. IEEE Access, 8, pp. 160268-160284. DOI: https://doi.org/10.1109/ACCESS.2020.3020638.
- Unceta Mendieta, I., Palacios, D., Nin Guerrero, J. & Pujol, O. (2020). Sampling unknown decision functions to build classifier copies. In Torra, V., Narukawa, Y. & Nin, J., Agell, N. (Eds.), Modeling Decisions for Artificial Intelligence - 17th International Conference, MDAI 2020, Proceedings (pp. 192-204). Springer. DOI: https://doi.org/10.1007/978-3-030-57524-3_16.
- Unceta Mendieta, I., Nin Guerrero, J. & Pujol, O. (2020). Transactional Compatible Representations for High Value Client Identification. In Barbosa, H., Menezes, R. & Gomez-Gardenes, J., Gonçalves, B., Mangioni, G., Oliveira, M. (Eds.), Complex Networks XI - Proceedings of the 11th Conference on Complex Networks, CompleNet 2020 (pp. 334-345). Springer. DOI: https://doi.org/10.1007/978-3-030-40943-2_28.
- Barja, A., Martínez, A., Arenas, A., Fleurquin, P., Nin Guerrero, J., Ramasco, J. J. & Tomás, E. (2019). Assessing the risk of default propagation in interconnected sectoral financial networks. EPJ Data Science, 8 (1), 32. DOI: https://doi.org/10.1140/epjds/s13688-019-0211-y.
- Arenas, A., Barja, A., Fleurquin, P., Martínez, A., Nin Guerrero, J., Ramasco, J. J. & Tomás, E. (2019). Assessing the risk of default propagation in interconnected sectoral financial networks. EPJ Data Science, 8, pp. 422-442. DOI: https://doi.org/10.1140/epjds/s13688-019-0211-y.
- Unceta Mendieta, I., Nin Guerrero, J. & Pujol, O. (2019). From batch to online learning using copies. In Sabater-Mir, J., Torra, V. & Aguilo, I., Gonzalez-Hidalgo, M. (Eds.), Artificial Intelligence Research and Development - Proceedings of the 22nd International Conference of the Catalan Association for Artificial Intelligence, CCIA 2019 (pp. 125-134). IOS Press. DOI: https://doi.org/10.3233/FAIA190115.
- Unceta Mendieta, I., Nin Guerrero, J. & Pujol, O. (2019). Using Copies to Remove Sensitive Data. In Morales, A., Fierrez, J. & Sánchez, J. S., Ribeiro, B. (Eds.), Pattern Recognition and Image Analysis - 9th Iberian Conference, IbPRIA 2019, Proceedings (pp. 182-193). Springer. DOI: https://doi.org/10.1007/978-3-030-31332-6_16.
- Nuñez-Del-Prado, M. & Nin Guerrero, J. (Accepted/In press). (2019). Revisiting online anonymization algorithms to ensure location privacy. Journal of Ambient Intelligence and Humanized Computing. DOI: https://doi.org/10.1007/s12652-019-01371-6.
- Nin Guerrero, J. & Tomás, E. (Accepted/In press). (2019). Default propagation in customer-supplier networks: An agent-based model approach to the isolation of companies in default. Journal of Ambient Intelligence and Humanized Computing. DOI: https://doi.org/10.1007/s12652-019-01370-7.
- Martínez, A., Nin Guerrero, J., Tomás, E. & Rubio, A. (2019). Graph convolutional networks on customer/supplier graph data to improve default prediction. Springer Proceedings in Complexity (pp. 135-146). Springer. DOI: https://doi.org/10.1007/978-3-030-14459-3_11.
- Aranda, J., Nin Guerrero, J. & Herranz, J. (2018). Answering Multiple Aggregate Queries under a Specific Privacy Condition. In Lung, C., Conte, T. & Liu, L., Akiyama, T., Hasan, K., Tovar, E., Takakura, H. (Eds.), Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018 (pp. 661-666). IEEE Computer Society. DOI: https://doi.org/10.1109/COMPSAC.2018.00099.
- Gómez, J. A., Arévalo, J., Paredes, R. & Nin Guerrero, J. (2018). End-to-end neural network architecture for fraud scoring in card payments. Pattern Recognition Letters, 105, pp. 175-181. DOI: https://doi.org/10.1016/j.patrec.2017.08.024.
- Nuñez-Del-Prado, M. & Nin Guerrero, J. (2018). On the Application of SDC Stream Methods to Card Payments Analytics. In Torra, V., Torra, V. & Narukawa, Y., González-Hidalgo, M., Aguilo, I. (Eds.), Modeling Decisions for Artificial Intelligence - 15th International Conference, MDAI 2018, Proceedings (pp. 306-318). Springer Verlag. DOI: https://doi.org/10.1007/978-3-030-00202-2_25.
- Martínez Rodríguez, D., Nin Guerrero, J. & Nuñez-Del-Prado, M. (2017). Towards the adaptation of SDC methods to stream mining. Computers and Security, 70, pp. 702-722. DOI: https://doi.org/10.1016/j.cose.2017.08.011.
- Guttler, F., Ienco, D., Nin Guerrero, J., Teisseire, M. & Poncelet, P. (2017). A graph-based approach to detect spatiotemporal dynamics in satellite image time series. ISPRS Journal of Photogrammetry and Remote Sensing, 130, pp. 92-107. DOI: https://doi.org/10.1016/j.isprsjprs.2017.05.013.
- Capdevila, J., Cerquides, J., Nin Guerrero, J. & Torres, J. (2017). Tweet-SCAN: An event discovery technique for geo-located tweets. Pattern Recognition Letters, 93, pp. 58-68. DOI: https://doi.org/10.1016/j.patrec.2016.08.010.
- Herranz, J., Nin Guerrero, J., Rodríguez, P. & Tassa, T. (2015). Revisiting distance-based record linkage for privacy-preserving release of statistical datasets. Data and Knowledge Engineering, 100, pp. 78-93. DOI: https://doi.org/10.1016/j.datak.2015.07.009.
- Sánchez-Charles, D., Muntés-Mulero, V., Solé, M. & Nin Guerrero, J. (2015). CrowdWON. Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015 (pp. 1284-1290). AI Access Foundation.
- Matwin, S., Nin Guerrero, J., Sehatkar, M. & Szapiro, T. (2015, January). A review of attribute disclosure control. Studies in Computational Intelligence, 567, pp. 41-61. DOI: https://doi.org/10.1007/978-3-319-09885-2_4.
- Capdevila, J., Cerquides, J., Nin Guerrero, J. & Torres, J. (2015). Tweet-SCAN. In Boixader, D., Grimaldo, F. & Armengol, E. (Eds.), Artificial Intelligence Research and Development - Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence (pp. 110-119). IOS Press. DOI: https://doi.org/10.3233/978-1-61499-578-4-110.
- Guttler, F., Alleaume, S., Corbane, C., Ienco, D., Nin Guerrero, J., Poncelet, P. & Teisseire, M. (2014). Exploring high repetitivity remote sensing time series for mapping and monitoring natural habitats - A new approach combining OBIA and k-partite graphs. International Geoscience and Remote Sensing Symposium IGARSS (pp. 3930-3933). Institute of Electrical and Electronics Engineers Inc.. DOI: https://doi.org/10.1109/IGARSS.2014.6947344.
- Herranz, J. & Nin Guerrero, J. (2014). Secure and efficient anonymization of distributed confidential databases. International Journal of Information Security, 13 (6), pp. 497-512. DOI: https://doi.org/10.1007/s10207-014-0237-x.
- Sánchez-Charles, D., Nin Guerrero, J., Solé, M. & Muntés-Mulero, V. (2014). Worker ranking determination in crowdsourcing platforms using aggregation functions. Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE (pp. 1801-1808). Institute of Electrical and Electronics Engineers Inc.. DOI: https://doi.org/10.1109/FUZZ-IEEE.2014.6891807.
- Balasch Masoliver, J., Muntés-Mulero, V. & Nin Guerrero, J. (2014). Using genetic algorithms for attribute grouping in multivariate microaggregation. Intelligent Data Analysis, 18, pp. 819-836. DOI: https://doi.org/10.3233/IDA-140670.
- Nin Guerrero, J., Tous, R. & Delgado, J. (2014). Variable linkage for multimedia metadata schema matching. Multimedia Tools and Applications, 68 (3), pp. 845-861. DOI: https://doi.org/10.1007/s11042-012-1094-0.
- Nin Guerrero, J. & Villatoro, D. (2014). Citizen in sensor networks. In Nin, J., Villatoro, D. (Ed.), Citizen in Sensor Networks - 2nd International Workshop, CitiSens 2013, Revised Selected Papers . Springer Verlag. DOI: https://doi.org/10.1007/978-3-319-04178-0.
- Nin Guerrero, J. & Villatoro, D. (2014). Preface. Lecture Notes in Computer Science including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 8313.
- Cea, D., Nin Guerrero, J., Tous, R., Torres, J. & Ayguadé, E. (2014). Towards the cloudification of the social networks analytics. In Torra, V., Narukawa, Y. & Endo, Y. (Eds.), Modeling Decisions forArtificial Intelligence - 11th International Conference, MDAI 2014, Proceedings (pp. 192-203). Springer Verlag. DOI: https://doi.org/10.1007/978-3-319-12054-6_17.
- Nin Guerrero, J. (2014). Beyond multivariate microaggregation for large record anonymization. In Nin, J., Villatoro, D. (Ed.), Citizen in Sensor Networks - 2nd International Workshop, CitiSens 2013, Revised Selected Papers (pp. 87-107). Springer Verlag. DOI: https://doi.org/10.1007/978-3-319-04178-0_8.
- Guttler, F., Ienco, D., Teisseire, M., Nin Guerrero, J. & Poncelet, P. (2014). Towards the Use of Sequential Patterns for Detection and Characterization of Natural and Agricultural Areas. Information Processing and Management of Uncertainty in Knowledge-Based Systems - 15th International Conference, IPMU 2014, Proceedings (PART 1 ed., pp. 97-106). Springer Verlag. DOI: https://doi.org/10.1007/978-3-319-08795-5_11.
- Nin Guerrero, J., Carrera, D. & Villatoro, D. (2014). On the use of social trajectory-based clustering methods for public transport optimization. In Nin, J., Villatoro, D. (Ed.), Citizen in Sensor Networks - 2nd International Workshop, CitiSens 2013, Revised Selected Papers (pp. 59-70). Springer Verlag. DOI: https://doi.org/10.1007/978-3-319-04178-0_6.
- Villatoro, D. & Nin Guerrero, J. (2013). Citizens sensor networks. Citizen in Sensor Networks - First International Workshop, CitiSens 2012, Revised Selected Papers (pp. 1-5). DOI: https://doi.org/10.1007/978-3-642-36074-9_1.
- Nin Guerrero, J. & Ricciardi, S. (2013). Digital watermarking techniques and security issues in the information and communication society. Proceedings - 27th International Conference on Advanced Information Networking and Applications Workshops, WAINA 2013 (pp. 1553-1558). DOI: https://doi.org/10.1109/WAINA.2013.171.
- Nin Guerrero, J. & Villatoro, D. (2013). Foreword from the citi sens 2012 program chairs. Lecture Notes in Computer Science including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 7685 LNAI.
- Rebollo-Monedero, D., Solé, M., Nin Guerrero, J. & Forné, J. (2013). A modification of the k-means method for quasi-unsupervised learning. Knowledge-Based Systems, 37, pp. 176-185. DOI: https://doi.org/10.1016/j.knosys.2012.07.024.
- Herranz, J., Nin Guerrero, J. & Solé, M. (2012). Kd-trees and the real disclosure risks of large statistical databases. Information Fusion, 13 (4), pp. 260-273. DOI: https://doi.org/10.1016/j.inffus.2011.03.001.
- Solé, M., Muntés-Mulero, V. & Nin Guerrero, J. (2012). Efficient microaggregation techniques for large numerical data volumes. International Journal of Information Security, 11 (4), pp. 253-267. DOI: https://doi.org/10.1007/s10207-012-0158-5.
- Herranz, J., Nin Guerrero, J. & Solé, M. (2012). More hybrid and secure protection of statistical data sets. IEEE Transactions on Dependable and Secure Computing, 9 (5), pp. 727-740. DOI: https://doi.org/10.1109/TDSC.2012.40.
- Peterson, B., Ricciardi, S. & Nin Guerrero, J. (2012). Energy-efficiency and security issues in the Cisco Nexus virtual distributed switching. Proceedings - 6th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2012 (pp. 552-557). DOI: https://doi.org/10.1109/IMIS.2012.60.
- Herranz, J., Nin Guerrero, J. & Solé, M. (2011). Optimal symbol alignment distance: A new distance for sequences of symbols. IEEE Transactions on Knowledge and Data Engineering, 23 (10), pp. 1541-1554. DOI: https://doi.org/10.1109/TKDE.2010.190.
- Tous, R., Nin Guerrero, J., Delgado, J. & Toran-Monserrat, P. (2011). Approaches and standards for metadata interoperability in distributed image search and retrieval. Database and Expert Systems Applications - 22nd International Conference, DEXA 2011, Proceedings (PART 2 ed., pp. 234-248). DOI: https://doi.org/10.1007/978-3-642-23091-2_21.
- Nin Guerrero, J., Laurent, A. & Poncelet, P. (2010). Speed up gradual rule mining from stream data! A B-Tree and OWA-based approach. Journal of Intelligent Information Systems, 35 (3), pp. 447-463. DOI: https://doi.org/10.1007/s10844-009-0112-9.
- Herranz, J., Matwin, S., Nin Guerrero, J. & Torra, V. (2010). Classifying data from protected statistical datasets. Computers and Security, 29 (8), pp. 875-890. DOI: https://doi.org/10.1016/j.cose.2010.05.005.
- Nin Guerrero, J. & Torra, V. (2010). Possibilistic reasoning for trust-based access control enforcement in social networks. 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 (5584646). DOI: https://doi.org/10.1109/FUZZY.2010.5584646.
- Herranz, J. & Nin Guerrero, J. (2010). Introduction to privacy and anonymity in information management systems. Advanced Information and Knowledge Processing (pp. 3-6). Springer-Verlag London Ltd. DOI: https://doi.org/10.1007/978-1-84996-238-4_1.
- Nin Guerrero, J., Herranz, J. & Torra, V. (2010). Using classification methods to evaluate attribute disclosure risk. Modeling Decisions for Artificial Intelligence - 7th International Conference, MDAI 2010, Proceedings (pp. 277-286). DOI: https://doi.org/10.1007/978-3-642-16292-3_27.
- Herranz, J., Nin Guerrero, J. & Torra, V. (2010). Distributed privacy-preserving methods for statistical disclosure control. Data Privacy Management and Autonomous Spontaneous Security - 4th International Workshop, DPM 2009, and Second International Workshop, SETOP 2009, Revised Selected Papers (pp. 33-47). DOI: https://doi.org/10.1007/978-3-642-11207-2_4.
- Nin Guerrero, J. & Torra, V. (2009). Towards the evaluation of time series protection methods. Information Sciences, 179 (11), pp. 1663-1677. DOI: https://doi.org/10.1016/j.ins.2009.01.024.
- Nin Guerrero, J. & Torra, V. (2009). Analysis of the univariate microaggregation disclosure risk. New Generation Computing, 27 (3), pp. 197-214. DOI: https://doi.org/10.1007/s00354-007-0061-1.
- Herranz, J. & Nin Guerrero, J. (2009). Partial symbol ordering distance. Modeling Decisions for Artificial Intelligence - 6th International Conference, MDAI 2009, Proceedings (pp. 293-302). DOI: https://doi.org/10.1007/978-3-642-04820-3_27.
- Valls, A., Nin Guerrero, J. & Torra, V. (2009). On the use of aggregation operators for location privacy. 2009 International Fuzzy Systems Association World Congress and 2009 European Society for Fuzzy Logic and Technology Conference, IFSA-EUSFLAT 2009 - Proceedings (pp. 489-494).
- Nin Guerrero, J., Salle, P., Bringay, S. & Teisseire, M. (2009). Using OWA operators for gene sequential pattern clustering. 2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009 (5255363). DOI: https://doi.org/10.1109/CBMS.2009.5255363.
- Herranz, J., Matwin, S., Meseguer, P. & Nin Guerrero, J. (2009). A cryptographic solution for private distributed simple meeting scheduling. Frontiers in Artificial Intelligence and Applications (1st ed., pp. 275-283). IOS Press. DOI: https://doi.org/10.3233/978-1-60750-061-2-275.
- Muntés-Mulero, V. & Nin Guerrero, J. (2009). Privacy and anonymization for very large datasets. ACM 18th International Conference on Information and Knowledge Management, CIKM 2009 (pp. 2117-2118). DOI: https://doi.org/10.1145/1645953.1646333.
- Nin Guerrero, J., Carminati, B., Ferrari, E. & Torra, V. (2009). Computing reputation for collaborative private networks. Proceedings - 2009 33rd Annual IEEE International Computer Software and Applications Conference, COMPSAC 2009 (pp. 246-253). DOI: https://doi.org/10.1109/COMPSAC.2009.40.
- Muntés-Mulero, V. & Nin Guerrero, J. (2009). International Conference on Information and Knowledge Management, Proceedings: Foreword. International Conference on Information and Knowledge Management, Proceedings, pp. iii.
- Nin Guerrero, J., Herranz, J. & Torra, V. (2008). On the disclosure risk of multivariate microaggregation. Data and Knowledge Engineering, 67 (3), pp. 399-412. DOI: https://doi.org/10.1016/j.datak.2008.06.014.
- Torra, V. & Nin Guerrero, J. (2008). Record linkage for database integration using fuzzy integrals. International Journal of Intelligent Systems, 23 (6), pp. 715-734. DOI: https://doi.org/10.1002/int.20293.
- Nin Guerrero, J., Herranz, J. & Torra, V. (2008). How to group attributes in multivariate microaggregation. International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, 16 (SUPPL. 1), pp. 121-138. DOI: https://doi.org/10.1142/S0218488508005285.
- Guisado-Gámez, J., Prat-Pérez, A., Nin Guerrero, J., Muntés-Mulero, V. & Larriba-Pey, J. L. (2008). Parallelizing record linkage for disclosure risk assessment. Privacy in Statistical Databases - UNESCO Chair in Data Privacy International Conference, PSD 2008, Proceedings (pp. 190-202). Springer Verlag. DOI: https://doi.org/10.1007/978-3-540-87471-3_16.
- Pont-Tuset, J., Nin Guerrero, J., Medrano-Gracia, P., Larriba-Pey, J. L. & Muntés-Mulero, V. (2008). Improving microaggregation for complex record anonymization. Modeling Decisions for Artificial Intelligence - 5th International Conference, MDAI 2008, Proceedings (pp. 215-226). Springer Verlag. DOI: https://doi.org/10.1007/978-3-540-88269-5_20.
- Nin Guerrero, J., Herranz, J. & Torra, V. (2008). Rethinking rank swapping to decrease disclosure risk. Data and Knowledge Engineering, 64 (1), pp. 346-364. DOI: https://doi.org/10.1016/j.datak.2007.07.006.
- Nin Guerrero, J., Herranz, J. & Torra, V. (2008). Towards a more realistic disclosure risk assessment. Privacy in Statistical Databases - UNESCO Chair in Data Privacy International Conference, PSD 2008, Proceedings (pp. 152-165). Springer Verlag. DOI: https://doi.org/10.1007/978-3-540-87471-3_13.
- Nin Guerrero, J., Herranz, J. & Torra, V. (2008). Attribute selection in multivariate microaggregation. PAIS'08 - Post-proceedings of the 2008 International Workshop on Privacy and Anonymity in Information Society, Co-located with EDBT 2008 (pp. 51-60). DOI: https://doi.org/10.1145/1379287.1379299.
- Pont-Tuset, J., Medrano-Gracia, P., Nin Guerrero, J., Larriba-Pey, J. L. & Muntés-Mulero, V. (2008). ONN the use of neural networks for data privacy. SOFSEM 2008 (pp. 634-645). Springer Verlag. DOI: https://doi.org/10.1007/978-3-540-77566-9_55.
- Nin Guerrero, J., Muntés-Mulero, V., MartíNez-Bazan, N. & Larriba-Pey, J. L. (2007). Semantic blocking for Record Linkage. Artificial Intelligence Research and Development (pp. 141-149).
- MartíNez-Bazan, N., Nin Guerrero, J., Muntés-Mulero, V., Sánchez-Martínez, M. A., Gómez-Villamor, S. & Larriba-Pey, J. L. (2007). DEX. CIKM 2007 - Proceedings of the 16th ACM Conference on Information and Knowledge Management (pp. 573-582). DOI: https://doi.org/10.1145/1321440.1321521.
- Nin Guerrero, J., Pont-Tuset, J., Medrano-Gracia, P., Larriba-Pey, J. L. & Muntés-Mulero, V. (2007). Increasing polynomial regression complexity for data anonymization. Proceedings The 2007 International Conference on Intelligent Pervasive Computing, IPC 2007 (pp. 29-34). DOI: https://doi.org/10.1109/IPC.2007.103.
- Medrano-Gracia, P., Pont-Tuset, J., Nin Guerrero, J. & Muntés-Mulero, V. (2007). Ordered data set vectorization for linear regression on data privacy. Modeling Decisions for Artificial Intelligence - 4th International Conference, MDAI 2007, Proceedings (pp. 361-372). Springer Verlag. DOI: https://doi.org/10.1007/978-3-540-73729-2_34.
- Nin Guerrero, J., Muntés-Mulero, V., MartíNez-Bazan, N. & Larriba-Pey, J. L. (2007). On the use of semantic blocking techniques for data cleansing and integration. 11th International Database Engineering and Applications Symposium Proceedings, IDEAS (pp. 190-198). DOI: https://doi.org/10.1109/IDEAS.2007.4318104.
- Nin Guerrero, J. & Torra, V. (2006). Distance based re-identification for time series, analysis of distances. In Domingo-Ferrer, J., Franconi, L. (Ed.), Privacy in Statistical Databases - CENEX-SDC Project International Conference, PSD 2006, Proceedings (pp. 205-216). Springer Verlag. DOI: https://doi.org/10.1007/11930242_18.
- Nin Guerrero, J. & Torra, V. (2006). New approach to the re-identification problem using neural networks. Modeling Decisions for Artificial Intelligence - Third International Conference, MDAI 2006, Proceedings (pp. 251-261). DOI: https://doi.org/10.1007/11681960_25.
- Nin Guerrero, J. & Torra, V. (2006). Extending microaggregation procedures for time series protection. Rough Sets and Current Trends in Computing - 5th International Conference, RSCTC 2006, Proceedings (pp. 899-908). Springer Verlag. DOI: https://doi.org/10.1007/11908029_93.
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