Data Mining & Databases

Published articles on data mining, knowledge discovery, database systems, and large-scale data analysis from OpenAlex.

Sample of the collection (25 of 99 items)

• Advanced Modelling of Soil Organic Carbon Content in Coal Mining Areas Using Integrated Spectral Analysis: A Dengcao Coal Mine Case Study Gill Ammara et al. Effective modelling and integrated spectral analysis approaches can advance modelling precision. To develop an integrated spectral…
• MetaboAnalyst 6.0: towards a unified platform for metabolomics data processing, analysis and interpretation McGill University We introduce MetaboAnalyst version 6.0 as a unified platform for processing, analyzing, and interpreting data from targeted as well as…
• ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support Central South University ADMETlab 3.0 is the second updated version of the web server that provides a comprehensive and efficient platform for evaluating…
• MixFormer: End-to-End Tracking with Iterative Mixed Attention Nanjing University Tracking often uses a multistage pipeline of feature extraction, target information integration, and bounding box estimation. To…
• SpectralFormer: Rethinking Hyperspectral Image Classification with Transformers Chinese Academy of Sciences Hyperspectral (HS) images are characterized by approximately contiguous spectral information, enabling the fine identification of…
• ZINC20—A Free Ultralarge-Scale Chemical Database for Ligand Discovery University of California, San Francisco Identifying and purchasing new small molecules to test in biological assays are enabling for ligand discovery, but as purchasable…
• The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data Lawrence Berkeley National Laboratory , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212…
• Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction University of Cambridge Organic synthesis is one of the key stumbling blocks in medicinal chemistry. A necessary yet unsolved step in planning synthesis is…
• Sustainable manufacturing in Industry 4.0: an emerging research agenda Chalmers University of Technology This systematic review intends to identify how sustainable manufacturing research is contributing to the development of the Industry 4.0…
• Crop Yield Prediction Using Deep Neural Networks Iowa State University Crop yield is a highly complex trait determined by multiple factors such as genotype, environment, and their interactions. Accurate…
• The IllustrisTNG simulations: public data release Max Planck Institute for Astrophysics Abstract We present the full public release of all data from the TNG100 and TNG300 simulations of the IllustrisTNG project. IllustrisTNG…
• Big Data and Predictive Analytics and Manufacturing Performance: Integrating Institutional Theory, Resource‐Based View and Big Data Culture Montpellier Business School Abstract The importance of big data and predictive analytics has been at the forefront of research for operations and manufacturing…
• A Survey on Digital Twin: Definitions, Characteristics, Applications, and Design Implications University of Brescia When, in 1956, Artificial Intelligence (AI) was officially declared a research field, no one would have ever predicted the huge…
• Supply chain risk management and artificial intelligence: state of the art and future research directions University of Huddersfield Supply chain risk management (SCRM) encompasses a wide variety of strategies aiming to identify, assess, mitigate and monitor unexpected…
• SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates Fritz Haber Institute of the Max Planck Society The lack of reliable methods for identifying descriptors---the sets of parameters capturing the underlying mechanisms of a material's…
• COCO-Stuff: Thing and Stuff Classes in Context University of Edinburgh Semantic classes can be either things (objects with a well-defined shape, e.g. car, person) or stuff (amorphous background regions, e.g.…
• Deep Learning Models for Wireless Signal Classification With Distributed Low-Cost Spectrum Sensors KU Leuven This paper looks into the modulation classification problem for a distributed wireless spectrum sensing network. First, a new…
• Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges Tsinghua University The widespread popularity of smart meters enables an immense amount of fine-grained electricity consumption data to be collected.…
• Learning under Concept Drift: A Review University of Technology Sydney Concept drift describes unforeseeable changes in the underlying distribution of streaming data overtime. Concept drift research involves…
• Long Short-Term Memory Network for Remaining Useful Life estimation The University of Texas at Arlington Remaining Useful Life (RUL) of a component or a system is defined as the length from the current time to the end of the useful life.…
• Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management University of Kassel Purpose Despite the variety of supply chain management (SCM) research, little attention has been given to the use of Big Data Analytics…
• Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The <i>R</i> Package <b>lcmm</b> Cécile Proust-Lima et al. The R package lcmm provides a series of functions to estimate statistical models based on linear mixed model theory. It includes the…
• An Overview and Deep Investigation on Sampled-Data-Based Event-Triggered Control and Filtering for Networked Systems Swinburne University of Technology This paper provides an overview and makes a deep investigation on sampled-data-based event-triggered control and filtering for networked…
• Convolutional Matrix Factorization for Document Context-Aware Recommendation Pohang University of Science and Technology Sparseness of user-to-item rating data is one of the major factors that deteriorate the quality of recommender system. To handle the…
• Critical analysis of Big Data challenges and analytical methods Brunel University of London Big Data (BD), with their potential to ascertain valued insights for enhanced decision-making process, have recently attracted…

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