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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A new approximate query engine based on intelligent capture and fast transformations of granulated data summaries
Dominik Ślęzak, Rick Glick, Paweł Betliński, et al.
Journal of Intelligent Information Systems (2017) Vol. 50, Iss. 2, pp. 385-414
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Cost Optimization for Big Data Workloads Based on Dynamic Scheduling and Cluster-Size Tuning
Marek Grzegorowski, Eftim Zdravevski, Andrzej Janusz, et al.
Big Data Research (2021) Vol. 25, pp. 100203-100203
Closed Access | Times Cited: 37
IEEE BigData 2019 Cup: Suspicious Network Event Recognition
Andrzej Janusz, Daniel Kałuża, Agnieszka Chądzyńska-Krasowska, et al.
2021 IEEE International Conference on Big Data (Big Data) (2019)
Closed Access | Times Cited: 32
Cluster-size optimization within a cloud-based ETL framework for Big Data
Eftim Zdravevski, Petre Lameski, Ace Dimitrievski, et al.
2021 IEEE International Conference on Big Data (Big Data) (2019)
Closed Access | Times Cited: 22
Applications of rough sets in big data analysis: An overview
Piotr Pięta, Tomasz Szmuc
International Journal of Applied Mathematics and Computer Science (2021) Vol. 31, Iss. 4
Open Access | Times Cited: 18
Scalable cyber-security analytics with a new summary-based approximate query engine
Dominik Ślęzak, Agnieszka Chądzyńska-Krasowska, Joel Holland, et al.
2021 IEEE International Conference on Big Data (Big Data) (2017), pp. 1840-1849
Closed Access | Times Cited: 22
HIFUN - a high level functional query language for big data analytics
Nicolas Spyratos, Tsuyoshi Sugibuchi
Journal of Intelligent Information Systems (2018) Vol. 51, Iss. 3, pp. 529-555
Closed Access | Times Cited: 10
Generating Fuzzy Linguistic Summaries for Menstrual Cycles
Łukasz Sosnowski, Tomasz Penza
Annals of Computer Science and Information Systems (2020) Vol. 21, pp. 119-128
Open Access | Times Cited: 8
Selected Aspects of Interactive Feature Extraction
Marek Grzegorowski
Lecture notes in computer science (2022), pp. 121-287
Closed Access | Times Cited: 5
Multivariate Ovulation Window Detection at OvuFriend
Joanna Fedorowicz, Łukasz Sosnowski, Dominik Ślęzak, et al.
Lecture notes in computer science (2019), pp. 395-408
Closed Access | Times Cited: 6
Considering various aspects of models’ quality in the ML pipeline - application in the logistics sector
Eyad Kannout, Michał Grodzki, Marek Grzegorowski
Annals of Computer Science and Information Systems (2022) Vol. 30, pp. 403-412
Open Access | Times Cited: 4
Ranking Mutual Information Dependencies in a Summary-based Approximate Analytics Framework
Dominik Ślęzak, Janusz Borkowski, Agnieszka Chądzyńska-Krasowska
(2018)
Closed Access | Times Cited: 5
Overlay Indexes: Efficiently Supporting Aggregate Range Queries and Authenticated Data Structures in Off-the-Shelf Databases
Diego Pennino, Maurizio Pizzonia, Alessio Papi
IEEE Access (2019) Vol. 7, pp. 175642-175670
Open Access | Times Cited: 5
Reinventing Infobright’s Concept of Rough Calculations on Granulated Tables for the Purpose of Accelerating Modern Data Processing Frameworks
Mateusz Wnuk, Sebastian Stawicki, Dominik Ślęzak
2021 IEEE International Conference on Big Data (Big Data) (2020), pp. 5405-5412
Closed Access | Times Cited: 4
Recursive Queries: Twenty-Five Years After SQL:1999
Marta Burzańska, Piotr Wiśniewski, Krzysztof Stencel
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 8272-8279
Closed Access
Premenstrual Syndrome Detection Based on Granular Computing and AI in Home Environment
Łukasz Sosnowski, Iwona Szymusik
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 8341-8350
Closed Access
Toward automatic assessment of a risk of women’s health disorders based on ontology decision models and menstrual cycle analysis
Łukasz Sosnowski, Jakub Wróblewski
2021 IEEE International Conference on Big Data (Big Data) (2021), pp. 5544-5552
Closed Access | Times Cited: 4
Similarity-based Detection of Fertile Days at OvuFriend
Łukasz Sosnowski, Wojciech Chaber, Łukasz Miłobędzki, et al.
2021 IEEE International Conference on Big Data (Big Data) (2018)
Closed Access | Times Cited: 3
Similarity-Based Accuracy Measures for Approximate Query Results
Agnieszka Chądzyńska-Krasowska
Communications in computer and information science (2018), pp. 515-527
Closed Access | Times Cited: 2
Approximate Decision Tree Induction over Approximately Engineered Data Features
Dominik Ślęzak, Agnieszka Chądzyńska-Krasowska
Lecture notes in computer science (2020), pp. 376-384
Open Access | Times Cited: 2
Rough Sets

Lecture notes in computer science (2018)
Closed Access | Times Cited: 1
Linguistically characterizing clusters of database query answers
Aurélien Moreau, Olivier Pivert, Grégory Smits
Fuzzy Sets and Systems (2019) Vol. 366, pp. 18-33
Open Access | Times Cited: 1
Study on Intelligent Analysis and Processing Technology of Computer Big Data Based on Clustering Algorithm
Rakesh Kumar ER, Xiaoming Liu, Md. Rokunojjaman, et al.
Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) (2022) Vol. 16, Iss. 2, pp. 150-158
Closed Access | Times Cited: 1
Toward Approximate Intelligence
Dominik Ślęzak
(2018)
Open Access
Approximating Aggregated SQL Queries With LSTM Networks
Nir Regev, Lior Rokach, Asaf Shabtai
arXiv (Cornell University) (2020)
Closed Access
Granular Computing
Davide Ciucci
Springer eBooks (2020), pp. 1-3
Closed Access
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