Pawel Boinski

Inf. Sci., 2025

2024

On tuning parameters guiding similarity computations in a data deduplication pipeline for customers records: Experience from a R&D project.

[BibT_eX]

[DOI]

Inf. Syst., March, 2024

Statistical Modeling vs. Machine Learning for Deduplication of Customer Records.

[BibT_eX]

[DOI]

Proceedings of the Workshops of the EDBT/ICDT 2024 Joint Conference co-located with the EDBT/ICDT 2024 Joint Conference, 2024

On Customer Data Deduplication - Research vs. Industrial Perspective: - Lessons Learned from a R&D Project in the Financial Sector.

[BibT_eX]

[DOI]

Proceedings of the New Trends in Database and Information Systems, 2024

2023

Maximal Mixed-Drove Co-occurrence Patterns.

[BibT_eX]

[DOI]

Inf. Syst. Frontiers, October, 2023

Bounding box representation of co-location instances for Chebyshev and Manhattan metrics.

[BibT_eX]

[DOI]

Data Knowl. Eng., May, 2023

On evaluating text similarity measures for customer data deduplication.

[BibT_eX]

[DOI]

Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

Text Similarity Measures in a Data Deduplication Pipeline for Customers Records.

[BibT_eX]

[DOI]

Proceedings of the 25th International Workshop on Design, 2023

On Tuning the Sorted Neighborhood Method for Record Comparisons in a Data Deduplication Pipeline - Industrial Experience Report.

[BibT_eX]

[DOI]

Proceedings of the Database and Expert Systems Applications, 2023

2022

On Customer Data Deduplication: Lessons Learned from a R&D Project in the Financial Sector.

[BibT_eX]

[DOI]

Waldemar Graniszewski

Proceedings of the Workshops of the EDBT/ICDT 2022 Joint Conference, 2022

2021

Bounding Box Representation of Co-location Instances for L<sub>∞ </sub> Induced Distance Measure.

[BibT_eX]

[DOI]

Proceedings of the Big Data Analytics and Knowledge Discovery, 2021

2019

Parallel approach to incremental co-location pattern mining.

[BibT_eX]

[DOI]

Inf. Sci., 2019

2018

Efficient spatial co-location pattern mining on multiple GPUs.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2018

2015

Parallel GPU-based Plane-Sweep Algorithm for Construction of iCPI-Trees.

[BibT_eX]

[DOI]

J. Database Manag., 2015

2014

Algorithms for spatial collocation pattern mining in a limited memory environment: a summary of results.

[BibT_eX]

[DOI]

J. Intell. Inf. Syst., 2014

A Parallel Algorithm for Building iCPI-trees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Databases and Information Systems, 2014

2013

Concurrent Execution of Data Mining Queries for Spatial Collocation Pattern Discovery.

[BibT_eX]

[DOI]

Proceedings of the Data Warehousing and Knowledge Discovery, 2013

GPU-Accelerated Collocation Pattern Discovery.

[BibT_eX]

[DOI]

Proceedings of the Advances in Databases and Information Systems, 2013

2012

Collocation Pattern Mining in a Limited Memory Environment Using Materialized iCPI-Tree.

[BibT_eX]

[DOI]

Proceedings of the Data Warehousing and Knowledge Discovery, 2012

Partitioning Approach to Collocation Pattern Mining in Limited Memory Environment Using Materialized iCPI-Trees.

[BibT_eX]

[DOI]

Proceedings of the Advances in Databases and Information Systems, 2012

2006

Improving Quality of Agglomerative Scheduling in Concurrent Processing of Frequent Itemset Queries.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Information Processing and Web Mining, 2006

A Greedy Approach to Concurrent Processing of Frequent Itemset Queries.

[BibT_eX]

[DOI]

Marek Wojciechowski