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Some Quality Concerns in the Big Data and Machine Learning Software Industry

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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cpe.3545openalex-extracted

Parallelization of a graph‐cut based algorithm for hierarchical clustering of web documents

inferredcites →https://doi.org/10.1002/cpe.4404openalex-extracted

A distributed parallel algorithm for inferring hierarchical groups from large‐scale text corpuses

inferredcites →https://doi.org/10.1002/cpe.5094openalex-extracted

Design and evaluation of a parallel document clustering algorithm based on hierarchical latent semantic analysis

inferredcites →https://doi.org/10.1007/11941439_114openalex-extracted

Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation

inferredcites →https://doi.org/10.1007/s11219-021-09557-yopenalex-extracted

Construction of a quality model for machine learning systems

inferredcites →https://doi.org/10.1007/s11227-015-1501-1openalex-extracted

A general perspective of Big Data: applications, tools, challenges and trends

inferredcites →https://doi.org/10.1007/s13198-022-01763-6openalex-extracted

Automatic hate speech detection using aspect based feature extraction and Bi-LSTM model

inferredcites →https://doi.org/10.1007/s13278-023-01025-8openalex-extracted

Identifying COVID-19 english informative tweets using limited labelled data

inferredcites →https://doi.org/10.1016/j.ipm.2015.06.006openalex-extracted

Design and evaluation of a parallel algorithm for inferring topic hierarchies

inferredcites →https://doi.org/10.1038/nature14539openalex-extracted

Deep learning

inferredcites →https://doi.org/10.1109/concapan.2017.8278488openalex-extracted

Refactoring improving the design of existing code

inferredcites →https://doi.org/10.1109/tkde.2013.109openalex-extracted

Data mining with big data

inferredcites →https://doi.org/10.1142/s0218194020400227openalex-extracted

Guidelines for Quality Assurance of Machine Learning-Based Artificial Intelligence

inferredcites →https://doi.org/10.1371/journal.pone.0177678openalex-extracted

Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric

inferredcites →https://doi.org/10.21125/iceri.2023.0530openalex-extracted

REACHING OUT TO STUDENTS IN AN UNDERGRADUATE ALGORITHMS CLASS: A TEACHERS’ PERSPECTIVE

inferredcites →https://doi.org/10.23876/j.krcp.2017.36.1.3openalex-extracted

Medical big data: promise and challenges

inferredcites →https://doi.org/10.48550/arxiv.2007.03606openalex-extracted

Data Science: A Comprehensive Overview

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.