Results 11 to 20 of about 5,859,578 (148)
On Classification of High-Cardinality Data Streams
SDM, 2010 The problem of massive-domain stream classification is one in which each attribute can take on one of a large number of possible values. Such streams often arise in applications such as IP monitoring, super-store transactions and financial data.
C. Aggarwal, Philip S. Yu
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New cardinality notations and styles for modeling NoSQL document-store databases
IEEE Region 10 Conference, 2017 Nowadays, data with several characteristics such as volume, variety etc. are generated daily, i.e. big data; its complexity cannot be overemphasized. On the other hand, schema free NoSQL databases keep emerging at almost the same phase to accommodate ...
A. A. Imam +4 more
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Transformasi Skema Basis Data Relasional Menjadi Model Data Berorientasi Dokumen pada MongoDB
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2016 MongoDB is a database that uses document-oriented data storage models. In fact, to migrate from a relational database to NoSQL databases such as MongoDB is not an easy matter especially if the data are extremely complex.
I Gede Winaya, Ahmad Ashari
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Analytics of Heterogeneous Breast Cancer Data Using Neuroevolution
IEEE Access, 2019 Breast cancer prognostic modeling is difficult since it is governed by many diverse factors. Given the low median survival and large scale breast cancer data, which comes from high throughput technology, the accurate and reliable prognosis of breast ...
Beibit Abdikenov +4 more
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Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2013 In this paper, we propose a method to estimate the probability distribution of the time interval which ellapses between the modifications of the cardinality in a random database query’s result set.
Velcescu Letitia
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High-cardinality categorical covariates in network regressions
Japanese Journal of Statistics and Data ScienceHigh-cardinality (nominal) categorical covariates are challenging in regression modeling, because they lead to high-dimensional models. For example, in generalized linear models (GLMs), categorical covariates can be implemented by dummy coding which ...
Ronald Richman, M. Wüthrich
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A unifying model for representing time-varying graphs [PDF]
International Conference on Data Science and Advanced Analytics, 2014 Graph-based models form a fundamental aspect of data representation in Data Sciences and play a key role in modeling complex networked systems. In particular, recently there is an ever-increasing interest in modeling dynamic complex networks, i.e ...
Klaus Wehmuth, A. Ziviani, E. Fleury
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Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic
Journal of Software and Systems Modeling, 2016 An enterprise database contains a global, integrated, and consistent representation of a company’s data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data
B. Neumayr +3 more
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MathematicsAs data-centric applications become increasingly complex, understanding effective query optimization in large-scale relational databases is crucial for managing this complexity.
Najla Sassi, Wassim Jaziri
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Multi-Criteria Fuzzy Portfolio Optimization Considering Varying Levels of Investor Expectations [PDF]
تحقیقات مالیObjectiveThe objective of the present research is the optimization of investment portfolios, considering all significant criteria for investors in a fuzzy environment, and taking into account various levels of investor expectations for each criterion ...
Ali Namaki +2 more
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