Results 221 to 230 of about 6,889,955 (273)

Survey of Cardinality Constraints in Snapshot and Temporal Semantic Data Models

, 2010
Cardinality captures necessary semantics in conceptual data modeling and determines how constructs are translated into relations. Business policies in a variety of domains like healthcare, education, supply chain management and geographic systems are often expressible in terms of cardinality.
Faiz Currim, Sudha Ram
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Using Machine Learning Models to Diagnose Chronic Rhinosinusitis: Analysis of Pre-Treatment Patient-Generated Health Data to Predict Cardinal Symptoms and Sinonasal Inflammation

American Journal of Rhinology & Allergy
Background The diagnosis of chronic rhinosinusitis (CRS) relies upon patient-reported symptoms and objective nasal endoscopy and/or computed tomography (CT) findings. Many patients, at the time of evaluation by an otolaryngologist or rhinologist, lack objective findings confirming CRS and do not have this disease.
Arun M. Raghavan, Mohamed A. Aboueisha, Ion Prohnitchi, David J. Cvancara, Ian M. Humphreys, Aria Jafari, Waleed M. Abuzeid   +6 more
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Including high-cardinality attributes in predictive models: A case study in churn prediction in the energy sector

Decision Support Systems, 2015
Julie Moeyersoms, David Martens
semanticscholar   +3 more sources

Analysis of Binary/Ternary Cardinality Combinations in Entity-Relationship Modeling

Data and Knowledge Engineering, 1996
Trevor H. Jones, I. Song
semanticscholar   +3 more sources

Complete Rules for n-Ary Relationship Cardinality Constraints

Data and Knowledge Engineering, 1998
A. McAllister
semanticscholar   +3 more sources

AdpDM: Adaptive Data Model for Efficient Dynamic Management of Large-Scale High-Cardinality Time-Series Databases

Ziyue Xu, Sutong Huang, Di Fei, Liping Yi, Chenfei Zhou, Gang Wang, Xiaoguang Liu, Xinyu Liu, Wenqing Yu, Zijing Wei, Shaozhi Liu   +10 more
openaire   +2 more sources

Non-Life Insurance Risk Classification Using Categorical Embedding

Social Science Research Network, 2022
This article presents several actuarial applications of categorical embedding in the context of non-life insurance risk classification. In non-life insurance, many rating factors are naturally categorical, and often the categorical variables have a large
Peng Shi, Kun Shi
semanticscholar   +1 more source

Study of Data Set Modelability: Modelability, Rivality, and Weighted Modelability Indexes

Journal of Chemical Information and Modeling, 2018
The knowledge of the capacity of a data set to be modeled in the first stages of the building of quantitative structure-activity relationship (QSAR) prediction models is an important issue because it might reduce the effort and time necessary to select ...
I. L. Ruiz, M. Gómez-Nieto
semanticscholar   +1 more source

Cancer microarray data feature selection using multi-objective binary particle swarm optimization algorithm

EXCLI Journal : Experimental and Clinical Sciences, 2016
Cancer investigations in microarray data play a major role in cancer analysis and the treatment. Cancer microarray data consists of complex gene expressed patterns of cancer.
Chandra Sekhara Rao Annavarapu, Suresh Dara, H. Banka   +2 more
semanticscholar   +1 more source

Actions Speak Louder than Words: Trillion-Parameter Sequential Transducers for Generative Recommendations

International Conference on Machine Learning
Large-scale recommendation systems are characterized by their reliance on high cardinality, heterogeneous features and the need to handle tens of billions of user actions on a daily basis.
Jiaqi Zhai, Lucy Liao, Xing Liu, Yueming Wang, Rui Li, Xuan Cao, Leon Gao, Zhaojie Gong, Fangda Gu, Michael He, Yin-Hua Lu, Yu Shi   +11 more
semanticscholar   +1 more source