Literatura académica sobre el tema "Data incompleteness"
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Artículos de revistas sobre el tema "Data incompleteness"
Acharya, Nanyan V., Lynda V. Wilton y Saad A. Shakir. "Incompleteness of Lamotrigine Data". Drug Safety 24, n.º 2 (2001): 155–56. http://dx.doi.org/10.2165/00002018-200124020-00005.
Texto completoMessenheimer, John A., Marcus E. Risner y Luigi Giorgi. "Incompleteness of Lamotrigine Data". Drug Safety 24, n.º 2 (2001): 155–56. http://dx.doi.org/10.2165/00002018-200124020-00006.
Texto completoMuris, Chris. "Efficient GMM Estimation with Incomplete Data". Review of Economics and Statistics 102, n.º 3 (junio de 2020): 518–30. http://dx.doi.org/10.1162/rest_a_00836.
Texto completoYi, Hui, Zehui Mao, Bin Jiang, Cuimei Bo, Yufang Liu y Hui Luo. "Fault Diagnosis in Condition of Sample Type Incompleteness Using Support Vector Data Description". Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/432651.
Texto completoTrovati, Marcello y Olayinka Johnny. "Big data inconsistencies and incompleteness: a literature review". International Journal of Grid and Utility Computing 11, n.º 5 (2020): 705. http://dx.doi.org/10.1504/ijguc.2020.10030948.
Texto completoJohnny, Olayinka y Marcello Trovati. "Big data inconsistencies and incompleteness: a literature review". International Journal of Grid and Utility Computing 11, n.º 5 (2020): 705. http://dx.doi.org/10.1504/ijguc.2020.110057.
Texto completoFlores, Jorge R. "Taxon incompleteness and discrete time bins affect character change rates in simulated data". Biology Letters 16, n.º 11 (noviembre de 2020): 20200418. http://dx.doi.org/10.1098/rsbl.2020.0418.
Texto completoSanz, Joaquin, Emanuele Cozzo, Javier Borge-Holthoefer y Yamir Moreno. "Topological effects of data incompleteness of gene regulatory networks". BMC Systems Biology 6, n.º 1 (2012): 110. http://dx.doi.org/10.1186/1752-0509-6-110.
Texto completoMarino-Buslje, Cristina, Alexander Miguel Monzon, Diego Javier Zea, María Silvina Fornasari y Gustavo Parisi. "On the dynamical incompleteness of the Protein Data Bank". Briefings in Bioinformatics 20, n.º 1 (2 de agosto de 2017): 356–59. http://dx.doi.org/10.1093/bib/bbx084.
Texto completoQi, Qianya, Li Yan y Lili Tian. "Testing equality of means in partially paired data with incompleteness in single response". Statistical Methods in Medical Research 28, n.º 5 (4 de abril de 2018): 1508–22. http://dx.doi.org/10.1177/0962280218765007.
Texto completoTesis sobre el tema "Data incompleteness"
Lembo, Domenico. "Dealing with Inconsistency and Incompleteness in Data Integration". Doctoral thesis, La Sapienza, 2004. http://hdl.handle.net/11573/917064.
Texto completoKarlsson, Peter S. "Issues of incompleteness, outliers and asymptotics in high dimensional data". Doctoral thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Economics, Finance and Statistics, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-14934.
Texto completoTang, Lie Ming. "Making Sense of Long-Term Physical Activity Tracker Data: The challenge of Incompleteness". Thesis, The University of Sydney, 2018. http://hdl.handle.net/2123/20996.
Texto completoNg, Yui-kin y 吳銳堅. "Computers, Gödel's incompleteness theorems and mathematics education: a study of the implications of artificialintelligence for secondary school mathematics". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1994. http://hub.hku.hk/bib/B31957419.
Texto completoSchintler, Laurie A. y Manfred M. Fischer. "The Analysis of Big Data on Cites and Regions - Some Computational and Statistical Challenges". WU Vienna University of Economics and Business, 2018. http://epub.wu.ac.at/6637/1/2018%2D10%2D28_Big_Data_on_cities_and_regions_untrack_changes.pdf.
Texto completoSeries: Working Papers in Regional Science
Thiele, Sven. "Modeling biological systems with Answer Set Programming". Phd thesis, Universität Potsdam, 2011. http://opus.kobv.de/ubp/volltexte/2012/5938/.
Texto completoIn den letzten Jahren wurden große Fortschritte bei der Identifikation und Messung der Bausteine des Lebens gemacht. Die Verfügbarkeit von Hochdurchsatzverfahren in der Molekularbiology hat das Anwachsen unseres biologischen Wissens dramatisch beschleunigt. Durch die technische Fortschritte in Genomic, Proteomic und Metabolomic wurde die Konstruktion komplexer Modelle biologischer Systeme ermöglicht. Immer mehr biologische Datenbanken sind über das Internet verfügbar, sie enthalten tausende Daten biochemischer Reaktionen und genetischer Regulation. System Biologie ist ein junger Forschungszweig der Biologie, der versucht Biologische Systeme in ihrer Ganzheit zu erforschen. Dabei ist man daran interessiert möglichst viel Wissen aus den unterschiedlichsten Bereichen in ein Modell zu aggregieren, welches das Zusammenwirken der verschiedensten Komponenten nachbildet. Durch das Studium derartiger Modelle erhofft man sich ein Verständnis der aufbauenden Eigenschaften, wie zum Beispiel Robustheit, des Systems zu erlangen. Es stellt sich jedoch die Problematik, das sowohl die biologischen Modelle als auch die verfügbaren Messwerte, oft unvollständig, miteinander unvereinbar oder fehlerhaft sind. All dies macht es schwierig biologisch sinnvolle Schlussfolgerungen zu ziehen. Daher, möchten wir in dieser Arbeit Antwortmengen Programmierung (engl. Answer Set Programming; ASP) als Werkzeug zur diskreten Modellierung system biologischer Probleme vorschlagen. ASP verfügt über eingebaute Eigenschaften zum Umgang mit unvollständiger Information, eine reichhaltige Modellierungssprache und hocheffiziente Berechnungstechniken. Wir präsentieren ASP Lösungen zur Analyse von Netzwerken genetischer Regulierungen, zur Prüfung der Konsistenz mit gemessene Daten, und zur Identifikation von Gründen für Inkonsistenz. Diesen Ansatz erweitern wir um die Möglichkeit zur Berechnung minimaler Reparaturen an Modell und Daten, welche Konsistenz erzeugen. Mithilfe dieser Methode werden wir in die Lage versetzt, auch im Fall von Inkonsistenz, noch ungemessene Daten vorherzusagen. Weiterhin, präsentieren wir einen ASP Ansatz zur Analyse metabolischer Netzwerke. Bei diesem Ansatz, nutzen wir zum einen aus das sich Erreichbarkeit mit ASP leicht spezifizieren lässt und das ASP mehrere mächtige Methoden zur Schlussfolgerung bereitstellt, welche sich auch kombiniert lassen. Dadurch wird es möglich die Synthese Möglichkeiten eines Metabolischen Netzwerks zu erforschen und Hypothesen für Erweiterungen des metabolischen Netzwerks zu berechnen. Zu guter Letzt, präsentieren wir die BioASP Softwarebibliothek. Die BioASP-Bibliothek kapselt unsere ASP Lösungen in das imperative Programmierparadigma und vereinfacht eine Integration von ASP Lösungen in heterogene Betriebsumgebungen, wie sie in der System Biologie vorherrschen.
Mecharnia, Thamer. "Approches sémantiques pour la prédiction de présence d'amiante dans les bâtiments : une approche probabiliste et une approche à base de règles". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG036.
Texto completoNowadays, Knowledge Graphs are used to represent all kinds of data and they constitute scalable and interoperable resources that can be used by decision support tools. The Scientific and Technical Center for Building (CSTB) was asked to develop a tool to help identify materials containing asbestos in buildings. In this context, we have created and populated the ASBESTOS ontology which allows the representation of building data and the results of diagnostics carried out in order to detect the presence of asbestos in the used products. We then relied on this knowledge graph to develop two approaches which make it possible to predict the presence of asbestos in products in the absence of the reference of the marketed product actually used.The first approach, called the hybrid approach, is based on external resources describing the periods when the marketed products are asbestos-containing to calculate the probability of the existence of asbestos in a building component. This approach addresses conflicts between external resources, and incompleteness of listed data by applying a pessimistic fusion approach that adjusts the calculated probabilities using a subset of diagnostics.The second approach, called CRA-Miner, is inspired by inductive logic programming (ILP) methods to discover rules from the knowledge graph describing buildings and asbestos diagnoses. Since the reference of specific products used during construction is never specified, CRA-Miner considers temporal data, ASBESTOS ontology semantics, product types and contextual information such as part-of relations to discover a set of rules that can be used to predict the presence of asbestos in construction elements.The evaluation of the two approaches carried out on the ASBESTOS ontology populated with the data provided by the CSTB show that the results obtained, in particular when the two approaches are combined, are quite promising
Rodriguez-Gianolli, Patricia. "Embracing Incompleteness in Schema Mappings". Thesis, 2013. http://hdl.handle.net/1807/35943.
Texto completoLibros sobre el tema "Data incompleteness"
Information, randomness & incompleteness: Papers on algorithmic information theory. 2a ed. Singapore: World Scientific, 1990.
Buscar texto completoInformation, randomness & incompleteness: Papers on algorithmic information theory. Singapore: World Scientific, 1987.
Buscar texto completoŚlusarski, Marek. Metody i modele oceny jakości danych przestrzennych. Publishing House of the University of Agriculture in Krakow, 2017. http://dx.doi.org/10.15576/978-83-66602-30-4.
Texto completoCapítulos de libros sobre el tema "Data incompleteness"
Jagadish⋆, Hosagrahar Visvesvaraya. "Incompleteness in Data Mining". En Advances in Knowledge Discovery and Data Mining, 1. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45357-1_1.
Texto completoThanisch, Peter, Tapio Niemi, Jyrki Nummenmaa, Zheying Zhang, Marko Niinimäki y Pertti Saariluoma. "Incompleteness in Conceptual Data Modelling". En Communications in Computer and Information Science, 159–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41947-8_15.
Texto completoLi, Qiang, Jianhua Li, Xiang Li y Shenghong Li. "Evaluation Incompleteness of Knowledge in Data Mining". En Content Computing, 278–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30483-8_33.
Texto completoMcArdle, John J. y John R. Nesselroade. "Contemporary data analyses based on planned incompleteness." En Longitudinal data analysis using structural equation models., 333–44. Washington: American Psychological Association, 2014. http://dx.doi.org/10.1037/14440-032.
Texto completoPeroncini, Roberto y Rita Pizzi. "Values for Some: How Does Criminal Network Undermine the Political System? A Data Mining Perspective". En Systemics of Incompleteness and Quasi-Systems, 267–82. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15277-2_21.
Texto completoGrzymala-Busse, Jerzy W. y Shantan R. Marepally. "Sensitivity and Specificity for Mining Data with Increased Incompleteness". En Artificial Intelligence and Soft Computing, 355–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13208-7_45.
Texto completoParry, Gareth W. "Incompleteness in Data Bases: Impact on Parameter Estimation Uncertainty". En Uncertainty in Risk Assessment, Risk Management, and Decision Making, 511–21. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4684-5317-1_40.
Texto completoGrzymala-Busse, Jerzy W. y Witold J. Grzymala-Busse. "Increasing Data Set Incompleteness May Improve Rule Set Quality". En Communications in Computer and Information Science, 200–216. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-05201-9_16.
Texto completoXu, Xian, Xiao Xu, Xiang Li y Guotong Xie. "GRMI: Graph Representation Learning of Multimodal Data with Incompleteness". En Database Systems for Advanced Applications, 286–96. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30675-4_19.
Texto completoGrzymala-Busse, Jerzy W. y Witold J. Grzymala-Busse. "Increasing Incompleteness of Data Sets—A Strategy for Inducing Better Rule Sets". En Advances in Machine Learning I, 345–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-05177-7_17.
Texto completoActas de conferencias sobre el tema "Data incompleteness"
Eliassi-rad, Tina, Rajmonda Caceres y Timothy LaRock. "Incompleteness in Networks". En KDD '19: The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3292500.3332276.
Texto completoScheglmann, Stefan, Gerd Groener, Steffen Staab y Ralf Lämmel. "Incompleteness-aware programming with RDF data". En the 2013 workshop. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2429376.2429380.
Texto completoChristodoulakis, Christina, Christos Faloutsos y Renee J. Miller. "VoidWiz: Resolving incompleteness using network effects". En 2014 IEEE 30th International Conference on Data Engineering (ICDE). IEEE, 2014. http://dx.doi.org/10.1109/icde.2014.6816748.
Texto completoMa, Z. M., W. J. Zhang, W. Y. Ma y G. Q. Chen. "Extending Express-G to Model Fuzzy Information in Product Data Model". En ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/cie-14620.
Texto completoLata, Kanchan y Shampa Chakraverty. "Handling data incompleteness using Rough Sets on multiple decision systems". En 2014 International Conference on Data Mining and Intelligent Computing (ICDMIC). IEEE, 2014. http://dx.doi.org/10.1109/icdmic.2014.6954243.
Texto completoChen, Jiayi y Aidong Zhang. "HGMF: Heterogeneous Graph-based Fusion for Multimodal Data with Incompleteness". En KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3394486.3403182.
Texto completoShaikh, Riaz Ahmed, Kamel Adi, Luigi Logrippo y Serge Mankovski. "Detecting incompleteness in access control policies using data classification schemes". En 2010 Fifth International Conference on Digital Information Management (ICDIM). IEEE, 2010. http://dx.doi.org/10.1109/icdim.2010.5664664.
Texto completoGurupur, Varadraj P., Muhammed Shelleh, Christopher Leone, Daniel Schupp-Omid, Roger Azevedo y Shashank Dubey. "THNN - A Neural Network Model for Telehealth Data Incompleteness Prediction". En 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2023. http://dx.doi.org/10.1109/embc40787.2023.10340989.
Texto completoChen, Jiayi y Aidong Zhang. "On Hierarchical Disentanglement of Interactive Behaviors for Multimodal Spatiotemporal Data with Incompleteness". En KDD '23: The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3580305.3599448.
Texto completo"IMPROVING QUALITY OF RULE SETS BY INCREASING INCOMPLETENESS OF DATA SETS - A Rough Set Approach". En 3rd International Conference on Software and Data Technologies. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001881902410248.
Texto completoInformes sobre el tema "Data incompleteness"
Bru Muñoz, María. The forgotten lender: the role of multilateral lenders in sovereign debt and default. Madrid: Banco de España, enero de 2023. http://dx.doi.org/10.53479/25026.
Texto completoSimakov, S. Evaluation of the Prompt Gamma-ray Spectrum from Spontaneous Fission of 252Cf. IAEA Nuclear Data Section, febrero de 2024. http://dx.doi.org/10.61092/iaea.bz1p-e3yc.
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