Cite

Aho, A.V., R. Sethi, and J.D. Ullman. 1986. Compilers: principles, techniques, and tools. Boston: Addison-Wesley Longman Publishing Co. Search in Google Scholar

Andrews, P.R. 2002. An Introduction to Mathematical Logic and Type Theory: To Truth Through Proof. Dordrecht: Kluwer Academic Publications. Search in Google Scholar

Axmark, D., and D. Widenius. 2021. MySQL 8.0 Reference Manual. Redwood Shores: Oracle Corporation. Available at: http://dev.mysql.com/doc/refman/8.0/en/ (accessed January 2023). Search in Google Scholar

Barendregt, H.P. 1984. The Lambda Calculus; Its Syntax and Semantics. Amsterdam: Elsevier Science B.V. Search in Google Scholar

Ben-Gan, I., and T. Moreau. 2000. Advanced Transact-SQL for SQL Server 2000. New York: Springer-Verlag. Search in Google Scholar

Bojanowski, P., E. Grave, A. Joulin, and T. Mikolov. 2017. “Enriching Word Vectors with Subword Information.” Transactions of the Association for Computational Linguistics 5: 135–146. DOI: https://doi.org/10.1162/tacl_a_00051. Search in Google Scholar

Brickley, D., and R.V. Guha. 2014. RDF Schema 1.1. Massachusetts: W3C. Available at: http://www.w3.org/TR/2014/REC-rdf-schema-20140225/ (accessed January 2023). Search in Google Scholar

Chollet, F. 2018. Deep Learning with Python. Shelter Island: Manning Publications Co. Search in Google Scholar

Codd, E.F. 1970. “A Relational Model of Data for Large Shared Data Banks.” Communications of the ACM 13: 377–387. DOI: https://doi.org/10.1145/362384.362685. Search in Google Scholar

Enderle, T., S. Giessing, and R. Tent. 2006. “Designing Confidentiality on the Fly Methodology – Three Aspects.” Proceedings of PSD LNCS 11126: 28–42. DOI: https://doi.org/10.1007/978-3-319-99771-1_3. Search in Google Scholar

Fraser B, and J. Wooton. 2006. “A proposed method for confidentialising tabular output to protect against differencing.” Monographs of Official Statistics. Work session on Statistical Data Confidentiality: 299–302. Luxembourg: Eurostat-Office for Official Publications of the European Communities. Corpus ID: 53573926. Search in Google Scholar

Gelsema, T. 2008. “General requirements for the soundness of metadata models.” Joint UNECE/Eurostat/OECD work session on statistical metadata (METIS). Available at: https://www.researchgate.net/publication/334708026_General_requirements_for_the_soundness_of_metadata_models (accessed January 2023). Search in Google Scholar

Gelsema, T. 2012. “The Organization of Information in a Statistical Office.” Journal of Official Statistics 28(3): 413–440. Available at: https://www.scb.se/contentassets/-ca21efb41fee47d293bbee5bf7be7fb3/the-organization-of-information-in-a-statistical-office.pdf. Search in Google Scholar

Gelsema, T. 2019. “The Logic of Aggregated Data.” Acta Cybernetica 24(2): 211–248. DOI: https://doi.org/10.14232/actacyb.24.2.2019.4. Search in Google Scholar

Geron, A. 2017. Hands-On Machine Learning with Scikit-Learn & Tensorflow. Sebastopol: O’Reilly Media Inc. Search in Google Scholar

Guo, J., Z. Zhan, Y. Xiao, J.G. Lou, T. Liu and D. Zhang. 2019. “Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representation.” DOI: https://doi.org/10.48550/arXiv.1905.08205. Search in Google Scholar

Hayes, P.J., and P.F. Patel-Schneider. 2014. RDF 1.1 Semantics. Massachusetts: W3C. Available at: http://www.w3.org/TR/2014/REC-rdf11-mt-20140225/ (accessed January 2023). Search in Google Scholar

Indurkhya, N., and F.J. Damerau. 2010. Handbook of Natural Language Processing, Second Edition. Boca Raton: Chapman & Hall/CRC. Search in Google Scholar

Ji, Z., Z.C. Lipton and C. Elkan. 2014. “Differential privacy and machine learning: a survey and review.” DOI: https://doi.org/10.48550/arXiv.1412.7584. Search in Google Scholar

Katsogiannis-Meimarakis, G., and G. Koutrika. 2021. “Deep Learning Approaches for Text-to-SQL Systems.” In Proceedings of the 24th International Conference on Extending Database Technology (EDBT), March 23–26: 710–713. Nicosia. Available at: https://openproceedings.org/2021/conf/edbt/p306.pdf (accessed January 2023). Search in Google Scholar

Kennet, R.S., and G. Shmueli. 2016. “From Quality to Information Quality in Official Statistics.” Journal of Official Statistics 32(4): 867–885. DOI: https://doi.org/10.1515/-jos-2016-0045. Search in Google Scholar

Marley, J.K., and V.L. Leaver. 2011. “A method for confidentialising user-defined tables: statistical properties and a risk-utility analysis.” In Proceedings of 58th World Statistical Congress: International Statistical Institute, Dublin. Available at: https://2011.isiproceedings.org (accessed January 2023). Search in Google Scholar

Meinke, K., and J.V. Tucker. 1992. “Universal Algebra.” In Handbook of Logic in Computer Science, Vol. I: Background; Mathematical Structures edited by S. Abramsky, M. Gabbay and T. Maibaum: 189–411. Oxford: Oxford Science Publications. Search in Google Scholar

Mikolov, T., K. Chen, G. Corrado, and J. Dean. 2013. “Efficient Estimation of Word Representations in Vector Space.” DOI: https://doi.org/10.48550/arXiv.1301.3781. Search in Google Scholar

Motik, B., P.F. Patel-Schneider and B. Cuenca Grau. 2012. OWL 2 Web Ontology Language Direct Semantics (Second Edition). Massachusetts: W3C. Available at: http://www.w3.org/TR/2012/REC-owl2-direct-semantics-20121211/ (accessed January 2023). Search in Google Scholar

Saha, D., A. Floratou, K. Sankaranarayanan, U. Farooq Minhas, A.R. Mittal and F. Ozcan. 2016. “ATHENA: An Ontology-Driven System for Natural Language Querying over Relational Data Stores.” In Proceedings of the VLDB Endowment 9(12): 1209–1220. Available at https://vldb.org/pvldb/vol9/p1209-saha.pdf (accessed January 2023). Search in Google Scholar

Thompson, G., S. Broadfoot, and D. Elazar. 2013. “Methodology for the automatic confidentialisation of statistical outputs from remote servers at the Autralian Bureau of Statistics.” Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality, October 28–30. Ottawa. Available at: https://unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2013/Topic_1_ABS.pdf (accessed January 2023). Search in Google Scholar

Vasiliev, Y. 2020. Natural Language Processing with Python and spaCy, A Practical Introduction. San Francisco: No Starch Press. Search in Google Scholar

Wang, B., R. Shin, X. Liu, O. Polozov, and M. Richardso. 2020. “RAT-SQL: Relation-Aware Schema Encoding, and Linking for Text-to-SQL Parsers.” DOI: https://doi.org/10.48550/arXiv.1911.04942. Search in Google Scholar

Weir, N., P. Utama, A. Galakatos, and A. Crotty. 2020. “DBPal: A Fully Pluggable NL2SQL Training Pipeline.” In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, June 14–19: 2347–2361. New York: Association for Computing Machinery. Available at: https://dl.acm.org/doi/10.1145/3318464.3380589 (accessed January 2023). Search in Google Scholar

Xu, X., C. Liu, and D. Song. 2017. “SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning.” DOI: https://doi.org/10.48550/arXiv.1711.04436. Search in Google Scholar

Zhong, V., C. Xiong, and R. Socher. 2017. “Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning.” DOI: https://doi.org/10.48550/arXiv.1709.00103. Search in Google Scholar

eISSN:
2001-7367
Idioma:
Inglés
Calendario de la edición:
4 veces al año
Temas de la revista:
Mathematics, Probability and Statistics