Výsledky vyhledávání - ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design/H.2.1.0: Data models

DynamicSchema: a lightweight persistency framework for context-oriented data management

Autoři: Castro, Sergio González, Sebastián Mens, Kim a další

Přispěvatelé: Castro, Sergio González, Sebastián Mens, Kim a další

Zdroj: COP '12 ; https://inria.hal.science/hal-00720348 ; COP '12, ACM, Jun 2012, Beijing, China. pp.5:1--5:6, ⟨10.1145/2307436.2307441⟩

Témata: ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design, ACM: H.: Information Systems/H.1: MODELS AND PRINCIPLES, ACM: H.: Information Systems/H.4: INFORMATION SYSTEMS APPLICATIONS, [INFO.INFO-PL]Computer Science [cs]/Programming Languages [cs.PL]

Geografické téma: Beijing, China

Dostupnost: https://inria.hal.science/hal-00720348
https://inria.hal.science/hal-00720348v1/document
https://inria.hal.science/hal-00720348v1/file/2012-cop-castro.pdf
https://doi.org/10.1145/2307436.2307441

Distributed XML Design

Autoři: Abiteboul, Serge Gottlob, Georg Manna, Marco a další

Přispěvatelé: Abiteboul, Serge Gottlob, Georg Manna, Marco a další

Zdroj: Symposium on Principles of Database Systems (PODS) ; https://hal.inria.fr/inria-00429591 ; Symposium on Principles of Database Systems (PODS), Jun 2009, Providence, United States. ⟨10.1145/1559795.1559833⟩

Témata: ACM: C.: Computer Systems Organization/C.2: COMPUTER-COMMUNICATION NETWORKS/C.2.4: Distributed Systems/C.2.4.2: Distributed databases, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design/H.2.1.0: Data models, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design/H.2.1.2: Schema and subschema, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]

Geografické téma: Providence, United States

Time: Providence, United States

Relation: info:eu-repo/grantAgreement/EC/FP7/226513/EU/Foundations of Web Data Management/WEBDAM; inria-00429591; https://hal.inria.fr/inria-00429591; https://hal.inria.fr/inria-00429591/document; https://hal.inria.fr/inria-00429591/file/p247-abiteboul.pdf

Dostupnost: https://hal.inria.fr/inria-00429591
https://hal.inria.fr/inria-00429591/document
https://hal.inria.fr/inria-00429591/file/p247-abiteboul.pdf
https://doi.org/10.1145/1559795.1559833

RDFViewS: A Storage Tuning Wizard for RDF Applications

Autoři: Goasdoué, François Karanasos, Konstantinos Leblay, Julien a další

Přispěvatelé: Goasdoué, François Karanasos, Konstantinos Leblay, Julien a další

Zdroj: ACM International Conference on Information and Knowledge Management ; https://inria.hal.science/inria-00509125 ; ACM International Conference on Information and Knowledge Management, Oct 2010, Toronto, Canada

Témata: RDF Data Management, View Selection, Materialized Views, Query Optimization, RDFS, ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.4: Systems and Software, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Geografické téma: Toronto

Time: Toronto, Canada

Relation: info:eu-repo/semantics/altIdentifier/arxiv/1008.2186; ARXIV: 1008.2186

Dostupnost: https://inria.hal.science/inria-00509125
https://inria.hal.science/inria-00509125v1/document
https://inria.hal.science/inria-00509125v1/file/cikm2010-karanasos.pdf

1. American Heart Association. (2021). Heart disease and stroke statistics—2021 update. Circulation, 143(8), e254-e743. 2. Rahman, M., Al Amin, M., Hasan, R., Hossain, S. T., Rahman, M. H., & Rashed, R. A. M. (2025). A Predictive AI Framework for Cardiovascular Disease Screening in the US: Integrating EHR Data with Machine and Deep Learning Models. British Journal of Nursing Studies, 5(2), 40-48. 3. ZakirHossain, M., Khan, M. M., Thapa, S., Uddin, R., Meem, E. J., Niloy, S. K., ... & Bhavani, G. D. (2025, February). Advanced Deep Learning Techniques for Precision Diagnosis of Tea Leaf Diseases. In 2025 IEEE International Conference on Emerging Technologies and Applications (MPSec ICETA) (pp. 1-6). IEEE. 4. Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining (pp. 785-794). ACM. 5. Damen, J. A., Hooft, L., Schuit, E., Debray, T. P., Collins, G. S., Tzoulaki, I., Lassale, C. M., Siontis, G. C., Chiocchia, V., Roberts, C., Schlüssel, M. M., Gerry, S., Black, J. A., Heus, P., van der Schouw, Y. T., Peelen, L. M., & Moons, K. G. (2016). Prediction models for cardiovascular disease risk in the general population: systematic review. BMJ, 353, i2416. 6. Framingham Heart Study. (1948). Framingham Heart Study cohort research data. National Heart, Lung, and Blood Institute. 7. Johnson, A. E., Pollard, T. J., Shen, L., Lehman, L. H., Feng, M., Ghassemi, M., Moody, B., Szolovits, P., Celi, L. A., & Mark, R. G. (2016). MIMIC-III, a freely accessible critical care database. Scientific Data, 3, 160035. 8. Krittanawong, C., Zhang, H., Wang, Z., Aydar, M., & Kitai, T. (2017). Artificial intelligence in precision cardiovascular medicine. Journal of the American College of Cardiology, 69(21), 2657-2664. 9. Lundberg, S. M., & Lee, S. I. (2017). A unified approach to interpreting model predictions. In Advances in Neural Information Processing Systems 30 (NIPS 2017) (pp. 4765-4774). 10. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., & Duchesnay, É. (2011). Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12, 2825–2830. 11. Shameer, K., Johnson, K. W., Glicksberg, B. S., Dudley, J. T., & Sengupta, P. P. (2018). Machine learning in cardiovascular medicine: are we there yet? Heart, 104(14), 1156-1164. 12. Steyerberg, E. W., Vergouwe, Y., & van Calster, B. (2019). Towards better clinical prediction models: seven steps for development and an ABCD for validation. European Heart Journal, 40(15), 1255–1264. 13. Sudlow, C., Gallacher, J., Allen, N., Beral, V., Burton, P., Danesh, J., Downey, P., Elliott, P., Green, J., Landray, M., Liu, B., Matthews, P., Ong, G., Pell, J., Silman, A., Young, A., Sprosen, T., Peakman, T., & Collins, R. (2015). UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLOS Medicine, 12(3), e1001779. 14. Weng, S. F., Reps, J., Kai, J., Garibaldi, J. M., & Qureshi, N. (2017). Can machine-learning improve cardiovascular risk prediction using routine clinical data? PLOS ONE, 12(4), e0174944. 15. World Health Organization. (2021). Cardiovascular diseases (CVDs). Retrieved from https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds) 16. Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., Kudlur, M., Levenberg, J., Monga, R., Moore, S., Murray, D. G., Steiner, B., Tucker, P., Vasudevan, V., Warden, P., ... Zheng, X. (2016). TensorFlow: A system for large-scale machine learning. In 12th USENIX symposium on operating systems design and implementation (OSDI 16) (pp. 265–283). 17. Chollet, F. (2015). Keras (Version 2.4.0) [Computer software]. https://github.com/fchollet/keras

Autoři: Okunola, Abiodun

Combining a Logical and a Numerical Method for Data Reconciliation

Autoři: Saïs, Fatiha Pernelle, Nathalie Rousset, Marie-Christine a další

Přispěvatelé: Saïs, Fatiha Pernelle, Nathalie Rousset, Marie-Christine a další

Zdroj: Lecture Notes in Computer Science ISBN: 9783642006845

Témata: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], ACM: H.: Information Systems, 0202 electrical engineering, electronic engineering, information engineering, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT, 02 engineering and technology, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.5: Heterogeneous Databases, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

Popis souboru: application/pdf

Přístupová URL adresa: http://membres-liglab.imag.fr/rousset/publis/article-JoDsXII.pdf
https://inria.hal.science/inria-00433007v1
https://hal.inria.fr/hal-00953252
https://rd.springer.com/chapter/10.1007%2F978-3-642-00685-2_3
https://hal.inria.fr/inria-00433007/document
https://link.springer.com/chapter/10.1007%2F978-3-642-00685-2_3
https://dblp.uni-trier.de/db/journals/jods/jods12.html#SaisPR09
https://doi.org/10.1007/978-3-642-00685-2_3

I/O Reference Behavior of Production Database Workloads and the TPC Benchmarks -- An Analysis at the Logical Level.

Autoři: Hsu, Windsor W. Smith, Alan Jay Young, Honesty C.

Zdroj: ACM Transactions on Database Systems; Mar2001, Vol. 26 Issue 1, p96-143, 48p

Témata: ARTIFICIAL intelligence, BENCHMARKING (Management), DATABASE management, ONLINE data processing, DECISION support systems, INFORMATION storage & retrieval systems

Comparing Representations with Relational and EER Models.

Autoři: Batra, Dinesh Hoffer, Jeffrey A. Bostrom, Robert P.

Zdroj: Communications of the ACM; Feb1990, Vol. 33 Issue 2, p126-139, 14p, 3 Diagrams, 4 Charts

Témata: INFORMATION storage & retrieval systems, DATABASE design, DATABASE management, ELECTRONIC data processing, INFORMATION technology, ERGONOMICS

Self-tuning Database Systems: A Systematic Literature Review of Automatic Database Schema Design and Tuning.

Autoři: Mozaffari, Maryam Dignös, Anton Gamper, Johann a další

Zdroj: ACM Computing Surveys; Nov2024, Vol. 56 Issue 11, p1-37, 37p

Témata: ARTIFICIAL intelligence, DATABASE management, DATABASE design, DATABASES, MODELING languages (Computer science), KNAPSACK problems, EVOLUTIONARY algorithms

A Model for Assisting Business Users along Analytical Processes

Autoři: Follenfant, Corentin Trastour, David Corby, Olivier a další

Přispěvatelé: Follenfant, Corentin Trastour, David Corby, Olivier a další

Zdroj: SPIM - 2nd Workshop on Semantic Personalized Information Management: Retrieval and Recommendation - 2012 ; https://inria.hal.science/hal-00759037 ; SPIM - 2nd Workshop on Semantic Personalized Information Management: Retrieval and Recommendation - 2012, Oct 2011, Bonn, Germany. pp.38-41 ; http://ceur-ws.org/Vol-781/paper5.pdf

Témata: business intelligence, content-based recommendation, analytical layers, usage semantics, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design/H.2.1.0: Data models, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design/H.2.1.2: Schema and subschema, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]

Geografické téma: Bonn, Germany

Dostupnost: https://inria.hal.science/hal-00759037
https://inria.hal.science/hal-00759037v1/document
https://inria.hal.science/hal-00759037v1/file/paper5_1_.pdf

A Unifying Approach to the Design of a Secure Database Operating System.

Autoři: Spooner, David L. Gudes, Ehud

Zdroj: IEEE Transactions on Software Engineering; May84, Vol. 10 Issue 3, p310-319, 10p, 2 Color Photographs, 2 Diagrams

Témata: DATABASE management, COMPUTER operating systems, DATA protection, COMPUTER interfaces, DATABASE design, COMPUTER security

FOREIGN KEYS DECREASE ADAPTABILITY OF DATABASE DESIGNS.

Autoři: Sibley, Edgar H. Wilmot, Richard B.

Zdroj: Communications of the ACM; Dec1984, Vol. 27 Issue 12, p1237-1243, 7p, 12 Diagrams

Témata: DATABASE design, DATABASE management, SYSTEMS design, ELECTRONIC data processing, DATABASES, INFORMATION science

Graph Pattern Matching in GQL and SQL/PGQ

Autoři: Deutsch, Alin Francis, Nadime Green, Alastair a další

Přispěvatelé: Deutsch, Alin Francis, Nadime Green, Alastair a další

Zdroj: SIGMOD '22: International Conference on Management of Data ; https://hal.science/hal-03688214 ; SIGMOD '22: International Conference on Management of Data, Jun 2022, Philadelphia, United States. ⟨10.1145/3514221.3526057⟩

Témata: Property graph, Graph database, SQL, Standardization, Pattern matching, Query language, GQL, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design/H.2.1.0: Data models, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.3: Languages/H.2.3.3: Query languages, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-DM]Computer Science [cs]/Discrete Mathematics [cs.DM], [INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO], [INFO.INFO-FL]Computer Science [cs]/Formal Languages and Automata Theory [cs.FL]

Geografické téma: United States

Time: Philadelphia, United States

Relation: info:eu-repo/semantics/altIdentifier/arxiv/2112.06217; ARXIV: 2112.06217

Dostupnost: https://hal.science/hal-03688214
https://doi.org/10.1145/3514221.3526057

Knowledge Representation for Model Management Systems.

Autoři: Dolk, Daniel R. Konsynski, Benn R.

Zdroj: IEEE Transactions on Software Engineering; Nov84, Vol. 10 Issue 6, p619-628, 10p, 2 Color Photographs, 8 Diagrams

Témata: DATABASE management, DECISION support systems, KNOWLEDGE management, KNOWLEDGE representation (Information theory), ARTIFICIAL intelligence, DATABASES

Continuous Graph Pattern Matching over Knowledge Graph Streams

Autoři: Gillani, Syed Picard, Gauthier Laforest, Frederique a další

Přispěvatelé: Gillani, Syed Picard, Gauthier Laforest, Frederique a další

Zdroj: ACM International Conference on Distributed and Event-Based Systems (DEBS) ; https://hal.science/hal-01310915 ; ACM International Conference on Distributed and Event-Based Systems (DEBS), Jun 2016, Irvine, California, United States. pp.214-225, ⟨10.1145/2933267.2933306⟩ ; http://debs2016.org

Témata: Knowledge graph, stream processing, incremental evaluation, RDF, semantic web, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.3: Languages/H.2.3.3: Query languages, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design/H.2.1.0: Data models, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.4: Systems/H.2.4.1: Distributed databases, [INFO.INFO-WB]Computer Science [cs]/Web, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]

Geografické téma: Irvine, California, United States

Dostupnost: https://hal.science/hal-01310915
https://doi.org/10.1145/2933267.2933306

Investigating the Relationship Between SLOC and Logical Database Measures to Improve the Early Estimation of Software Cost.

Autoři: Tokdemir, Gul Cagiltay, Nergiz Ercil

Zdroj: International Journal of Software Engineering & Knowledge Engineering; Mar2019, Vol. 29 Issue 3, p401-413, 13p

Témata: DATABASE design, DATABASE management software, COMPUTER software, SYSTEMS software, COMPUTER software development

Heuristic Optimization of Physical Data Bases: Using a Generic and Abstract Design Model.

Autoři: Palvia, Prashant

Zdroj: Decision Sciences; Summer88, Vol. 19 Issue 3, p564-579, 16p, 1 Diagram, 2 Charts, 3 Graphs

Témata: HEURISTIC, OPERATIONS research, DATABASES, MATHEMATICAL programming, MANAGEMENT information systems, DATABASE management

The Role of Domain Ontologies in Database Design: An Ontology Management and Conceptual Modeling Environment.

Autoři: Sugumaran, Vijayan Storey, Veda C.

Zdroj: ACM Transactions on Database Systems; Sep2006, Vol. 31 Issue 3, p1064-1094, 31p

Témata: DATABASE design, ONTOLOGY, SYSTEMS design, DATABASE management, ELECTRONIC information resources, ENTITY-relationship modeling, INFORMATION modeling

Database Skeleton and Its Application to Logical Database Synthesis.

Autoři: Shi-Kuo Chang Wu-Haung Cheng

Zdroj: IEEE Transactions on Software Engineering; Jan78, Vol. 4 Issue 1, p18-30, 13p, 13 Diagrams, 3 Charts

Témata: DATABASES, DATABASE design, SYSTEMS design, COMPUTER systems, ELECTRONIC systems, COMPUTER software, SOFTWARE engineering

PHYSICAL DESIGN: EQUIVALENCIES IN DATABASE CONVERSION.

Autoři: Gillenson, Mark L. Sibley, Edgar H.

Zdroj: Communications of the ACM; Aug1990, Vol. 33 Issue 8, p120-131, 12p, 8 Diagrams

Témata: DATABASE design, DATABASE management

Logical Representation of a Conceptual Model for Spatial Data Warehouses.

Autoři: Malinowski, Elzbieta Zimányi, Esteban

Zdroj: GeoInformatica; Dec2007, Vol. 11 Issue 4, p431-457, 27p, 5 Diagrams

Témata: SPATIAL data infrastructures, CONCEPTUAL models, GEOGRAPHIC information systems, MANAGEMENT information systems, DATABASE management, DATA warehousing