Suchergebnisse - acm: h.: information system/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

Autoren: Castro, Sergio González, Sebastián Mens, Kim et al.

Weitere Verfasser: Castro, Sergio González, Sebastián Mens, Kim et al.

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

Schlagwörter: 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]

Geographisches Schlagwort: Beijing, China

Verfügbarkeit: 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

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

Autoren: Okunola, Abiodun

Distributed XML Design

Autoren: Abiteboul, Serge Gottlob, Georg Manna, Marco et al.

Weitere Verfasser: Abiteboul, Serge Gottlob, Georg Manna, Marco et al.

Quelle: 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⟩

Schlagwörter: 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]

Geographisches Schlagwort: 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

Verfügbarkeit: 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

Autoren: Goasdoué, François Karanasos, Konstantinos Leblay, Julien et al.

Weitere Verfasser: Goasdoué, François Karanasos, Konstantinos Leblay, Julien et al.

Quelle: 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

Schlagwörter: 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]

Geographisches Schlagwort: Toronto

Time: Toronto, Canada

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

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

Combining a Logical and a Numerical Method for Data Reconciliation

Autoren: Saïs, Fatiha Pernelle, Nathalie Rousset, Marie-Christine et al.

Weitere Verfasser: Saïs, Fatiha Pernelle, Nathalie Rousset, Marie-Christine et al.

Quelle: Lecture Notes in Computer Science ISBN: 9783642006845

Schlagwörter: [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]

Dateibeschreibung: application/pdf

Zugangs-URL: 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.

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

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

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

Graph Pattern Matching in GQL and SQL/PGQ

Autoren: Deutsch, Alin Francis, Nadime Green, Alastair et al.

Weitere Verfasser: Deutsch, Alin Francis, Nadime Green, Alastair et al.

Quelle: 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⟩

Schlagwörter: 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]

Geographisches Schlagwort: United States

Time: Philadelphia, United States

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

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

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

Autoren: Spooner, David L. Gudes, Ehud

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

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

Comparing Representations with Relational and EER Models.

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

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

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

Online Reorganization of Databases.

Autoren: SOCKUT, GARY H. IYER, BALAKRISHNA R.

Quelle: ACM Computing Surveys; Jul2009, Vol. 41 Issue 3, p14.1-14.136, 136p, 5 Diagrams, 2 Charts

Schlagwörter: ONLINE databases, DATABASES, SQL, DATABASE management, DATABASE design, DATABASE searching

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

Autoren: Mozaffari, Maryam Dignös, Anton Gamper, Johann et al.

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

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

FOREIGN KEYS DECREASE ADAPTABILITY OF DATABASE DESIGNS.

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

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

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

PHYSICAL DESIGN: EQUIVALENCIES IN DATABASE CONVERSION.

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

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

Schlagwörter: DATABASE design, DATABASE management

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

Autoren: Sugumaran, Vijayan Storey, Veda C.

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

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

Continuous Graph Pattern Matching over Knowledge Graph Streams

Autoren: Gillani, Syed Picard, Gauthier Laforest, Frederique et al.

Weitere Verfasser: Gillani, Syed Picard, Gauthier Laforest, Frederique et al.

Quelle: 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

Schlagwörter: 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]

Geographisches Schlagwort: Irvine, California, United States

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

Query-oriented Summarization of RDF Graphs

Autoren: Čebirić, Šejla Goasdoué, François Manolescu, Ioana et al.

Weitere Verfasser: Čebirić, Šejla Goasdoué, François Manolescu, Ioana et al.

Quelle: Data Engineering Meets Semantic Web Workshop (DESWeb) ; https://inria.hal.science/hal-01179484 ; Data Engineering Meets Semantic Web Workshop (DESWeb), Apr 2015, Seoul, South Korea ; http://desweb2015.imis.athena-innovation.gr

Schlagwörter: Semantic Web, summarization, RDF data manipulation, RDF Data Management, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.3: Languages, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.1: Logical Design, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]

Geographisches Schlagwort: Seoul, South Korea

Verfügbarkeit: https://inria.hal.science/hal-01179484

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

Autoren: Tokdemir, Gul Cagiltay, Nergiz Ercil

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

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

Knowledge Representation for Model Management Systems.

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

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

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

Logical Representation of a Conceptual Model for Spatial Data Warehouses.

Autoren: Malinowski, Elzbieta Zimányi, Esteban

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

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

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

Autoren: Palvia, Prashant

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

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