Minakshi Kaushik

Orcid: 0000-0002-6658-1712

Affiliations:
  • Tallinn University of Technology, Estonia


According to our database1, Minakshi Kaushik authored at least 17 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Discretizing Numerical Attributes: An Analysis of Human Perceptions.
CoRR, 2023

Numerical Association Rule Mining: A Systematic Literature Review.
CoRR, 2023

On Observing Patterns of Correlations During Drill-Down.
Proceedings of the Information Integration and Web Intelligence, 2023

2022
A Novel Framework for Unification of Association Rule Mining, Online Analytical Processing and Statistical Reasoning.
IEEE Access, 2022

An Analysis of Human Perception of Partitions of Numerical Factor Domains.
Proceedings of the Information Integration and Web Intelligence, 2022

Detecting Simpson's Paradox: A Machine Learning Perspective.
Proceedings of the Database and Expert Systems Applications, 2022

Towards Unification of Statistical Reasoning, OLAP and Association Rule Mining: Semantics and Pragmatics.
Proceedings of the Database Systems for Advanced Applications, 2022

Why Not to Trust Big Data: Discussing Statistical Paradoxes.
Proceedings of the Database Systems for Advanced Applications. DASFAA 2022 International Workshops, 2022

Exploring Factors in a Crossroad Dataset Using Cluster-Based Association Rule Mining.
Proceedings of the 13th International Conference on Ambient Systems, 2022

Discretizing Numerical Attributes: An Analysis of Human Perceptions.
Proceedings of the New Trends in Database and Information Systems, 2022

Detecting Simpson's Paradox: A Step Towards Fairness in Machine Learning.
Proceedings of the New Trends in Database and Information Systems, 2022

2021
A Systematic Assessment of Numerical Association Rule Mining Methods.
SN Comput. Sci., 2021

Impact-Driven Discretization of Numerical Factors: Case of Two- and Three-Partitioning.
Proceedings of the Big Data Analytics - 9th International Conference, 2021

Big Data Analytics in Association Rule Mining: A Systematic Literature Review.
Proceedings of the BDET 2021: The 3rd International Conference on Big Data Engineering and Technology, 2021

2020
On the Potential of Numerical Association Rule Mining.
Proceedings of the Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications, 2020

Expected vs. Unexpected: Selecting Right Measures of Interestingness.
Proceedings of the Big Data Analytics and Knowledge Discovery, 2020

Grand Reports: A Tool for Generalizing Association Rule Mining to Numeric Target Values.
Proceedings of the Big Data Analytics and Knowledge Discovery, 2020


  Loading...