Relevant bibliographies by topics / Data incompleteness

Academic literature on the topic 'Data incompleteness'

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Published: 25 May 2024

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Journal articles on the topic "Data incompleteness"

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Acharya, Nanyan V., Lynda V. Wilton, and Saad A. Shakir. "Incompleteness of Lamotrigine Data." Drug Safety 24, no. 2 (2001): 155–56. http://dx.doi.org/10.2165/00002018-200124020-00005.

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Messenheimer, John A., Marcus E. Risner, and Luigi Giorgi. "Incompleteness of Lamotrigine Data." Drug Safety 24, no. 2 (2001): 155–56. http://dx.doi.org/10.2165/00002018-200124020-00006.

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Muris, Chris. "Efficient GMM Estimation with Incomplete Data." Review of Economics and Statistics 102, no. 3 (June 2020): 518–30. http://dx.doi.org/10.1162/rest_a_00836.

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In the standard missing data model, data are either complete or completely missing. However, applied researchers face situations with an arbitrary number of strata of incompleteness. Examples include unbalanced panels and instrumental variables settings where some observations are missing some instruments. I propose a model for settings where observations may be incomplete, with an arbitrary number of strata of incompleteness. I derive a set of moment conditions that generalizes those in Graham's ( 2011 ) standard missing data setup. I derive the associated efficiency bound and propose efficient estimators. Identification can be achieved even if it fails in each stratum of incompleteness.
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Yi, Hui, Zehui Mao, Bin Jiang, Cuimei Bo, Yufang Liu, and 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.

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Faulty samples are much harder to acquire than normal samples, especially in complicated systems. This leads to incompleteness for training sample types and furthermore a decrease of diagnostic accuracy. In this paper, the relationship between sample-type incompleteness and the classifier-based diagnostic accuracy is discussed first. Then, a support vector data description-based approach, which has taken the effects of sample-type incompleteness into consideration, is proposed to refine the construction of fault regions and increase the diagnostic accuracy for the condition of incomplete sample types. The effectiveness of the proposed method was validated on both a Gaussian distributed dataset and a practical dataset. Satisfactory results have been obtained.
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Trovati, Marcello, and Olayinka Johnny. "Big data inconsistencies and incompleteness: a literature review." International Journal of Grid and Utility Computing 11, no. 5 (2020): 705. http://dx.doi.org/10.1504/ijguc.2020.10030948.

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Johnny, Olayinka, and Marcello Trovati. "Big data inconsistencies and incompleteness: a literature review." International Journal of Grid and Utility Computing 11, no. 5 (2020): 705. http://dx.doi.org/10.1504/ijguc.2020.110057.

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Flores, Jorge R. "Taxon incompleteness and discrete time bins affect character change rates in simulated data." Biology Letters 16, no. 11 (November 2020): 20200418. http://dx.doi.org/10.1098/rsbl.2020.0418.

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Estimating how fast or slow morphology evolves through time (phenotypic change rate, PR) has become common in macroevolutionary studies and has been important for clarifying key evolutionary events. However, the inclusion of incompletely scored taxa (e.g. fossils) and variable lengths of discrete arbitrary time bins could affect PR estimates and potentially mask real PR patterns. Here, the impact of taxon incompleteness (unscored data) on PR estimates is assessed in simulated data. Three different time bin series were likewise evaluated: bins evenly spanning the tree length (i), a shorter middle bin and longer first and third bins (ii), and a longer middle bin and shorter first and third bins (iii). The results indicate that PR values decrease as taxon incompleteness increases. Statistically significant PR values, and the dispersion among PR values, depended on the time bins. These outcomes imply that taxon incompleteness can undermine our capacity to infer morphology evolutionary dynamics and that these estimates are also influenced by our choice of discrete time bins. More importantly, the present results stress the need for a better approach to deal with taxon incompleteness and arbitrary discrete time bins.
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Sanz, Joaquin, Emanuele Cozzo, Javier Borge-Holthoefer, and Yamir Moreno. "Topological effects of data incompleteness of gene regulatory networks." BMC Systems Biology 6, no. 1 (2012): 110. http://dx.doi.org/10.1186/1752-0509-6-110.

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Marino-Buslje, Cristina, Alexander Miguel Monzon, Diego Javier Zea, María Silvina Fornasari, and Gustavo Parisi. "On the dynamical incompleteness of the Protein Data Bank." Briefings in Bioinformatics 20, no. 1 (August 2, 2017): 356–59. http://dx.doi.org/10.1093/bib/bbx084.

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Qi, Qianya, Li Yan, and Lili Tian. "Testing equality of means in partially paired data with incompleteness in single response." Statistical Methods in Medical Research 28, no. 5 (April 4, 2018): 1508–22. http://dx.doi.org/10.1177/0962280218765007.

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In testing differentially expressed genes between tumor and healthy tissues, data are usually collected in paired form. However, incomplete paired data often occur. While extensive statistical researches exist for paired data with incompleteness in both arms, hardly any recent work can be found on paired data with incompleteness in single arm. This paper aims to fill this gap by proposing some new methods, namely, P-value pooling methods and a nonparametric combination test. Simulation studies are conducted to investigate the performance of the proposed methods in terms of type I error and power at small to moderate sample sizes. A real data set from The Cancer Genome Atlas (TCGA) breast cancer study is analyzed using the proposed methods.
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Dissertations / Theses on the topic "Data incompleteness"

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Lembo, Domenico. "Dealing with Inconsistency and Incompleteness in Data Integration." Doctoral thesis, La Sapienza, 2004. http://hdl.handle.net/11573/917064.

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Karlsson, 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.

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This thesis consists of four individual essays and an introduction chapter. The essays are in the field of multivariate statistical analysis of High dimensional data. The first essay presents the issue of estimating the inverse covariance matrix alone and when it is used within the Mahalanobis distance in High-dimensional data. Three types of ridge-shrinkage estimators of the inverse covariance matrix are suggested and evaluated through Monte Carlo simulations. The second essay deals with incomplete observations in empirical applications of the Arbitrage Pricing Theory model and the interest is to model the underlying covariance structure among the variables by a few common factors. Two possible solutions to the problem are considered and a case study using the Swedish OMX data is conducted for demonstration. In the third essay the issue of outlier detection in High-dimensional data is treated. A number of point estimators of the Mahalanobis distance are suggested and their properties are evaluated. In the fourth and last essay the relation between the second central moment of a distribution to its first raw moment is considered in an financial context. Three possible estimators are considered and it is shown that they are consistent even when the dimension increases proportionally to the number of observations.
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Tang, 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.

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Millions of people have already collected weeks, months and even years of data about their own health and physical activity levels. The potential is enormous for use in personal applications as well as for public health analysis of large populations at low cost. However, the reality is many people fail to wear their tracker and record data all day every day especially over the long-term. The resulting incompleteness in data poses an important challenge for interpreting long-term tracker data, in terms of both making sense of it and in dealing with the uncertainty of inferences based on it. Surprisingly, there has been little work into defining the problem, its extent and how it should be measured and addressed. This thesis tackles this key challenge and we demonstrate the need for a term to describe and quantify this challenge. We introduce the term, adherence, which quantifies the completeness in such data. We also offer interface designs that accounted for adherence to support self-monitoring and reflection. Bringing these together, we provide broader definitions and guidelines for incorporating adherence when making sense of long-term physical activity tracker data, both in personal applications and in public health research results. This thesis is based on three studies. First is a semester-long study of tracker use by 237 University students. Second is a study of 21 existing long-term physical activity trackers and provided the first richly qualitative exploration of physical activity and adherence of such users. It also evaluated the iStuckWithIt, a long-term physical activity data user interface, and reported on insights gained within and as aided by a tutorial and reflection scaffolding. In the final study, we drew on 12 diverse datasets, for 753 users, with over 77,000 days with data and 73,000 days missing to explore the impact of different definitions of adherence and methods for dealing with its implications.
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Ng, Yui-kin, and 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.

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Schintler, Laurie A., and 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.

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Big Data on cities and regions bring new opportunities and challenges to data analysts and city planners. On the one side, they hold great promise to combine increasingly detailed data for each citizen with critical infrastructures to plan, govern and manage cities and regions, improve their sustainability, optimize processes and maximize the provision of public and private services. On the other side, the massive sample size and high-dimensionality of Big Data and their geo-temporal character introduce unique computational and statistical challenges. This chapter provides overviews on the salient characteristics of Big Data and how these features impact on paradigm change of data management and analysis, and also on the computing environment.
Series: Working Papers in Regional Science
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Thiele, Sven. "Modeling biological systems with Answer Set Programming." Phd thesis, Universität Potsdam, 2011. http://opus.kobv.de/ubp/volltexte/2012/5938/.

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Biology has made great progress in identifying and measuring the building blocks of life. The availability of high-throughput methods in molecular biology has dramatically accelerated the growth of biological knowledge for various organisms. The advancements in genomic, proteomic and metabolomic technologies allow for constructing complex models of biological systems. An increasing number of biological repositories is available on the web, incorporating thousands of biochemical reactions and genetic regulations. Systems Biology is a recent research trend in life science, which fosters a systemic view on biology. In Systems Biology one is interested in integrating the knowledge from all these different sources into models that capture the interaction of these entities. By studying these models one wants to understand the emerging properties of the whole system, such as robustness. However, both measurements as well as biological networks are prone to considerable incompleteness, heterogeneity and mutual inconsistency, which makes it highly non-trivial to draw biologically meaningful conclusions in an automated way. Therefore, we want to promote Answer Set Programming (ASP) as a tool for discrete modeling in Systems Biology. ASP is a declarative problem solving paradigm, in which a problem is encoded as a logic program such that its answer sets represent solutions to the problem. ASP has intrinsic features to cope with incompleteness, offers a rich modeling language and highly efficient solving technology. We present ASP solutions, for the analysis of genetic regulatory networks, determining consistency with observed measurements and identifying minimal causes for inconsistency. We extend this approach for computing minimal repairs on model and data that restore consistency. This method allows for predicting unobserved data even in case of inconsistency. Further, we present an ASP approach to metabolic network expansion. This approach exploits the easy characterization of reachability in ASP and its various reasoning methods, to explore the biosynthetic capabilities of metabolic reaction networks and generate hypotheses for extending the network. Finally, we present the BioASP library, a Python library which encapsulates our ASP solutions into the imperative programming paradigm. The library allows for an easy integration of ASP solution into system rich environments, as they exist in Systems Biology.
In 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.
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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.

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De nos jours, les Graphes de Connaissances sont utilisés pour représenter toutes sortes de données et ils constituent des ressources évolutives, interopérables et exploitables par des outils d’aide à la décision. Le Centre Scientifique et Technique du Bâtiment (CSTB) a été sollicité pour développer un outil d'aide à l'identification des matériaux contenant de l'amiante dans les bâtiments. Dans ce contexte, nous avons créé et peuplé l'ontologie ASBESTOS qui permet la représentation des données des bâtiments et les résultats des diagnostics réalisés en vue de détecter la présence d’amiante dans les produits utilisés. Nous nous sommes ensuite basés sur ce graphe de connaissance pour développer deux approches qui permettent de prédire la présence d’amiante dans les produits en l’absence de la référence du produit commercialisé effectivement utilisé.La première approche, nommée approche hybride, se base sur des ressources externes décrivant les périodes où les produits commercialisés sont amiantés pour calculer une probabilité d’existence d’amiante dans un composant du bâtiment. Cette approche traite les conflits entre les ressources externes, et l’incomplétude des données répertoriées en appliquant une approche de fusion pessimiste qui ajuste les probabilités calculées en utilisant un sous-ensemble de diagnostiques.La deuxième approche, nommée CRA-Miner, s’inspire de méthodes de programmation logique inductive (PLI) pour découvrir des règles à partir du graphe de connaissances décrivant les bâtiments et les diagnostics d'amiante. La référence des produits spécifiques utilisés lors de la construction n'étant jamais spécifiée, CRA-Miner considère les données temporelles, la sémantique de l'ontologie ASBESTOS, les types de produits et les informations contextuelles telles que les relations partie-tout pour découvrir un ensemble de règles qui pourront être utilisées pour prédire la présence d'amiante dans les éléments de construction.L’évaluation des deux approches menées sur l'ontologie ASBESTOS peuplée avec les données fournies par le CSTB montrent que les résultats obtenus, en particulier quand les deux approches sont combinées, sont tout à fait prometteurs
Nowadays, 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
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Rodriguez-Gianolli, Patricia. "Embracing Incompleteness in Schema Mappings." Thesis, 2013. http://hdl.handle.net/1807/35943.

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Various forms of information integration have become ubiquitous in current Business Intelligence (BI) technologies. In many cases, the semantic relationship between heterogeneous data sources is specified using high-level declarative rules, called schema mappings. For decades, Skolem functions have been regarded as an important tool in schema mappings as they permit a precise representation of incomplete information. The powerful mapping language of second-order tuple generating dependencies (SO tgds) permits arbitrary Skolem functions and has been proven to be the right class for modeling many integration problems, such as composition and correlation of mappings. This language is strictly more powerful than the languages used in many integration systems, including source-to-target and nested tgds which are both first-order (FO) languages (commonly known as GLAV and nested GLAV mappings). An important class of GLAV mappings are Local-As-View (LAV) tgds, which has found important application in data integration. These FO mapping languages are known to have more desirable programmatic and computational properties. In this thesis, we present a number of techniques for translating some SO tgds into equivalent, more manageable FO schema mappings. Our results rely on understanding and controlling the presence of incompleteness in mappings. We show that the composition of LAV mappings is not only FO, but can always be expressed as a LAV mapping. As a byproduct, we show that the problem of recovery checking for LAV mappings becomes tractable, in contrast to the case of GLAV mappings for which it is known to be undecidable. We introduce two approaches for transforming SO tgds into equivalent nested GLAV mappings. Our approach considers the presence of source constraints, and provides sufficient conditions for when the rich Skolem functions in SO tgds are well-behaved and have an FO semantics. We experimentally show that these conditions are able to handle a very large number of real schema mappings. Last, we propose a first-step for embracing incompleteness in the context of BI applications. Specifically, we present elements of a formal framework for vivifying data with respect to a business model. We view the task of discovering data-to-business interpretations as one of removing incompleteness from these mappings.
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Books on the topic "Data incompleteness"

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Information, randomness & incompleteness: Papers on algorithmic information theory. 2nd ed. Singapore: World Scientific, 1990.

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Information, randomness & incompleteness: Papers on algorithmic information theory. Singapore: World Scientific, 1987.

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Ślusarski, 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.

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The quality of data collected in official spatial databases is crucial in making strategic decisions as well as in the implementation of planning and design works. Awareness of the level of the quality of these data is also important for individual users of official spatial data. The author presents methods and models of description and evaluation of the quality of spatial data collected in public registers. Data describing the space in the highest degree of detail, which are collected in three databases: land and buildings registry (EGiB), geodetic registry of the land infrastructure network (GESUT) and in database of topographic objects (BDOT500) were analyzed. The results of the research concerned selected aspects of activities in terms of the spatial data quality. These activities include: the assessment of the accuracy of data collected in official spatial databases; determination of the uncertainty of the area of registry parcels, analysis of the risk of damage to the underground infrastructure network due to the quality of spatial data, construction of the quality model of data collected in official databases and visualization of the phenomenon of uncertainty in spatial data. The evaluation of the accuracy of data collected in official, large-scale spatial databases was based on a representative sample of data. The test sample was a set of deviations of coordinates with three variables dX, dY and Dl – deviations from the X and Y coordinates and the length of the point offset vector of the test sample in relation to its position recognized as a faultless. The compatibility of empirical data accuracy distributions with models (theoretical distributions of random variables) was investigated and also the accuracy of the spatial data has been assessed by means of the methods resistant to the outliers. In the process of determination of the accuracy of spatial data collected in public registers, the author’s solution was used – resistant method of the relative frequency. Weight functions, which modify (to varying degree) the sizes of the vectors Dl – the lengths of the points offset vector of the test sample in relation to their position recognized as a faultless were proposed. From the scope of the uncertainty of estimation of the area of registry parcels the impact of the errors of the geodetic network points was determined (points of reference and of the higher class networks) and the effect of the correlation between the coordinates of the same point on the accuracy of the determined plot area. The scope of the correction was determined (in EGiB database) of the plots area, calculated on the basis of re-measurements, performed using equivalent techniques (in terms of accuracy). The analysis of the risk of damage to the underground infrastructure network due to the low quality of spatial data is another research topic presented in the paper. Three main factors have been identified that influence the value of this risk: incompleteness of spatial data sets and insufficient accuracy of determination of the horizontal and vertical position of underground infrastructure. A method for estimation of the project risk has been developed (quantitative and qualitative) and the author’s risk estimation technique, based on the idea of fuzzy logic was proposed. Maps (2D and 3D) of the risk of damage to the underground infrastructure network were developed in the form of large-scale thematic maps, presenting the design risk in qualitative and quantitative form. The data quality model is a set of rules used to describe the quality of these data sets. The model that has been proposed defines a standardized approach for assessing and reporting the quality of EGiB, GESUT and BDOT500 spatial data bases. Quantitative and qualitative rules (automatic, office and field) of data sets control were defined. The minimum sample size and the number of eligible nonconformities in random samples were determined. The data quality elements were described using the following descriptors: range, measure, result, and type and unit of value. Data quality studies were performed according to the users needs. The values of impact weights were determined by the hierarchical analytical process method (AHP). The harmonization of conceptual models of EGiB, GESUT and BDOT500 databases with BDOT10k database was analysed too. It was found that the downloading and supplying of the information in BDOT10k creation and update processes from the analyzed registers are limited. An effective approach to providing spatial data sets users with information concerning data uncertainty are cartographic visualization techniques. Based on the author’s own experience and research works on the quality of official spatial database data examination, the set of methods for visualization of the uncertainty of data bases EGiB, GESUT and BDOT500 was defined. This set includes visualization techniques designed to present three types of uncertainty: location, attribute values and time. Uncertainty of the position was defined (for surface, line, and point objects) using several (three to five) visual variables. Uncertainty of attribute values and time uncertainty, describing (for example) completeness or timeliness of sets, are presented by means of three graphical variables. The research problems presented in the paper are of cognitive and application importance. They indicate on the possibility of effective evaluation of the quality of spatial data collected in public registers and may be an important element of the expert system.
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Book chapters on the topic "Data incompleteness"

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Jagadish⋆, Hosagrahar Visvesvaraya. "Incompleteness in Data Mining." In 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.

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Thanisch, Peter, Tapio Niemi, Jyrki Nummenmaa, Zheying Zhang, Marko Niinimäki, and Pertti Saariluoma. "Incompleteness in Conceptual Data Modelling." In 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.

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Li, Qiang, Jianhua Li, Xiang Li, and Shenghong Li. "Evaluation Incompleteness of Knowledge in Data Mining." In Content Computing, 278–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30483-8_33.

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McArdle, John J., and John R. Nesselroade. "Contemporary data analyses based on planned incompleteness." In Longitudinal data analysis using structural equation models., 333–44. Washington: American Psychological Association, 2014. http://dx.doi.org/10.1037/14440-032.

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Peroncini, Roberto, and Rita Pizzi. "Values for Some: How Does Criminal Network Undermine the Political System? A Data Mining Perspective." In 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.

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Grzymala-Busse, Jerzy W., and Shantan R. Marepally. "Sensitivity and Specificity for Mining Data with Increased Incompleteness." In 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.

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Parry, Gareth W. "Incompleteness in Data Bases: Impact on Parameter Estimation Uncertainty." In 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.

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Grzymala-Busse, Jerzy W., and Witold J. Grzymala-Busse. "Increasing Data Set Incompleteness May Improve Rule Set Quality." In 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.

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Xu, Xian, Xiao Xu, Xiang Li, and Guotong Xie. "GRMI: Graph Representation Learning of Multimodal Data with Incompleteness." In Database Systems for Advanced Applications, 286–96. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30675-4_19.

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Grzymala-Busse, Jerzy W., and Witold J. Grzymala-Busse. "Increasing Incompleteness of Data Sets—A Strategy for Inducing Better Rule Sets." In 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.

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Conference papers on the topic "Data incompleteness"

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Eliassi-rad, Tina, Rajmonda Caceres, and Timothy LaRock. "Incompleteness in Networks." In 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.

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Scheglmann, Stefan, Gerd Groener, Steffen Staab, and Ralf Lämmel. "Incompleteness-aware programming with RDF data." In the 2013 workshop. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2429376.2429380.

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Christodoulakis, Christina, Christos Faloutsos, and Renee J. Miller. "VoidWiz: Resolving incompleteness using network effects." In 2014 IEEE 30th International Conference on Data Engineering (ICDE). IEEE, 2014. http://dx.doi.org/10.1109/icde.2014.6816748.

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Ma, Z. M., W. J. Zhang, W. Y. Ma, and G. Q. Chen. "Extending Express-G to Model Fuzzy Information in Product Data Model." In 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.

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Abstract Information with uncertainty and imprecision is inherently presented in engineering design and manufacturing. The nature of uncertainty and imprecision is incompleteness. The incompleteness is a typical feature in earlier product design phases. Product design is essentially viewed as a process of reducing the incompleteness in the description of conceptual design. Some methods and strategies for the preliminary engineering design, calculation, and modeling in relational database systems have been proposed to process imprecise and uncertain information. Product data model, being a core of intelligent manufacturing system, consists of all concerned data in the product life cycle. EXPRESS-G is a powerful tool to develop a product data model. This paper extends the EXPRESS-G to make it possible to represent information with uncertainty and imprecision.
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Lata, Kanchan, and Shampa Chakraverty. "Handling data incompleteness using Rough Sets on multiple decision systems." In 2014 International Conference on Data Mining and Intelligent Computing (ICDMIC). IEEE, 2014. http://dx.doi.org/10.1109/icdmic.2014.6954243.

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Chen, Jiayi, and Aidong Zhang. "HGMF: Heterogeneous Graph-based Fusion for Multimodal Data with Incompleteness." In 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.

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Shaikh, Riaz Ahmed, Kamel Adi, Luigi Logrippo, and Serge Mankovski. "Detecting incompleteness in access control policies using data classification schemes." In 2010 Fifth International Conference on Digital Information Management (ICDIM). IEEE, 2010. http://dx.doi.org/10.1109/icdim.2010.5664664.

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Gurupur, Varadraj P., Muhammed Shelleh, Christopher Leone, Daniel Schupp-Omid, Roger Azevedo, and Shashank Dubey. "THNN - A Neural Network Model for Telehealth Data Incompleteness Prediction." In 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.

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Chen, Jiayi, and Aidong Zhang. "On Hierarchical Disentanglement of Interactive Behaviors for Multimodal Spatiotemporal Data with Incompleteness." In 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.

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"IMPROVING QUALITY OF RULE SETS BY INCREASING INCOMPLETENESS OF DATA SETS - A Rough Set Approach." In 3rd International Conference on Software and Data Technologies. SciTePress - Science and and Technology Publications, 2008. http://dx.doi.org/10.5220/0001881902410248.

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Reports on the topic "Data incompleteness"

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Bru Muñoz, María. The forgotten lender: the role of multilateral lenders in sovereign debt and default. Madrid: Banco de España, January 2023. http://dx.doi.org/10.53479/25026.

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The role of multilateral lenders in sovereign default has been traditionally overlooked by the literature. However, these creditors represent a significant share of lending to emerging markets and feature very distinct characteristics, such as lower interest rates and seniority. By including these creditors in a traditional DSGE model of sovereign default, I reproduce the high debt levels found in the data while maintaining default probabilities within realistic values. Additionally, I am able to analyze the role of multilateral debt in emerging economies. Multilateral loans complement private financing and reduce the incompleteness of international financial markets. Also, multilateral funding acts as an insurance mechanism in bad times, providing countries with some degree of consumption smoothing, opposite to the role of front-loading consumption fulfilled by private financing.
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Simakov, S. Evaluation of the Prompt Gamma-ray Spectrum from Spontaneous Fission of 252Cf. IAEA Nuclear Data Section, February 2024. http://dx.doi.org/10.61092/iaea.bz1p-e3yc.

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The energy spectra, multiplicities and average energies of the prompt, total and delayed γ-rays accompanying the spontaneous fission of 252Cf were collected from the literature and dedicated databases. They were carefully analysed for consistency with a view to producing reference data for usage in various applications. This could be accomplished for the prompt fission gamma ray spectrum up to 20 MeV since dozens of measurements exist and reasonably agree. The prompt fission gamma ray spectrum (PFGS) was non-model evaluated by fitting the preselected experimental data with the help of the generalized least-squares (GLS) code GMA. The resulting spectrum could be considered as a reference for the γ-ray energies from 0.1 to 20 MeV with uncertainties varying between ≈ 3 and 25%. This reference gamma spectrum will be a substantial contribution to the precise and complete characterisation of the 252Cf source since the prompt fission neutron spectrum (PFNS), which has been accepted as a standard for a long time, has comparable uncertainties. The average gamma multiplicity and energy were also surveyed and used to derive the recommended values. The prompt X- and γ-ray energy spectra below ≈ 100 keV and delayed photon spectra in the whole energy range, as well as their multiplicities, are still seldomly and incompletely measured, that excepts an evaluation based on experimental data. The comparison with existing theoretical prompt and delayed 252Cf(s.f.) γ-spectra or with those presented in the major evaluated cross section libraries explored their incompleteness or deviations from the evaluated PFGS. The existing measurements of the pionic and muonic radioactivity of 252Cf(s.f.) and 235U(nth,f) were reviewed and the potential impact of gammas from the π0 decay on the high energy part of the PFGS was investigated.
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