| Efficient spatial co-location pattern mining on multiple GPUs W Andrzejewski, P Boinski Expert Systems with Applications 93, 465-483, 2018 | 39 | 2018 |
| Parallel approach to incremental co-location pattern mining W Andrzejewski, P Boinski Information Sciences 496, 485-505, 2019 | 30 | 2019 |
| Parallel GPU-based plane-sweep algorithm for construction of iCPI-trees W Andrzejewski, P Boinski Journal of Database Management (JDM) 26 (3), 1-20, 2015 | 20 | 2015 |
| GPU-accelerated collocation pattern discovery W Andrzejewski, P Boinski East European Conference on Advances in Databases and Information Systems …, 2013 | 15 | 2013 |
| Collocation pattern mining in a limited memory environment using materialized iCPI-tree P Boinski, M Zakrzewicz International Conference on Data Warehousing and Knowledge Discovery, 279-290, 2012 | 15 | 2012 |
| On customer data deduplication: Lessons learned from a r&d project in the financial sector P Boiński, M Sienkiewicz, B Bębel, R Wrembel, D Gałęzowski, ... CEUR Workshop Proceedings 3135, 2022 | 11 | 2022 |
| Algorithms for spatial collocation pattern mining in a limited memory environment: a summary of results P Boinski, M Zakrzewicz Journal of Intelligent Information Systems 43, 147-182, 2014 | 9 | 2014 |
| Text Similarity Measures in a Data Deduplication Pipeline for Customers Records. W Andrzejewski, B Bebel, P Boinski, M Sienkiewicz, R Wrembel DOLAP, 33-42, 2023 | 8 | 2023 |
| A parallel algorithm for building iCPI-trees W Andrzejewski, P Boinski East European Conference on Advances in Databases and Information Systems …, 2014 | 8 | 2014 |
| RNA-Puzzles Round V: blind predictions of 23 RNA structures F Bu, Y Adam, RW Adamiak, M Antczak, BRH de Aquino, NG Badepally, ... Nature methods 22 (2), 399-411, 2025 | 6 | 2025 |
| On Tuning the Sorted Neighborhood Method for Record Comparisons in a Data Deduplication Pipeline: Industrial Experience Report P Boiński, W Andrzejewski, B Bębel, R Wrembel International Conference on Database and Expert Systems Applications, 164-178, 2023 | 5 | 2023 |
| On evaluating text similarity measures for customer data deduplication P Boinski, M Sienkiewicz, R Wrembel, B Bebel, W Andrzejewski Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 297-300, 2023 | 5 | 2023 |
| Partitioning Approach to Collocation Pattern Mining in Limited Memory Environment Using Materialized iCPI-Trees P Boinski, M Zakrzewicz Advances in Databases and Information Systems, 19-30, 2013 | 5 | 2013 |
| Hash Join Based Spatial Collocation Pattern Mining P Boiński, M Zakrzewicz Foundations of Computing and Decision Sciences 36, 3-15, 2011 | 5 | 2011 |
| A greedy approach to concurrent processing of frequent itemset queries P Boinski, M Wojciechowski, M Zakrzewicz International Conference on Data Warehousing and Knowledge Discovery, 292-301, 2006 | 5 | 2006 |
| On tuning parameters guiding similarity computations in a data deduplication pipeline for customers records: Experience from a R&D project W Andrzejewski, B Bębel, P Boiński, R Wrembel Information Systems 121, 102323, 2024 | 4 | 2024 |
| Maximal mixed-drove co-occurrence patterns W Andrzejewski, P Boinski Information Systems Frontiers 25 (5), 2005-2028, 2023 | 3 | 2023 |
| Improving Quality of Agglomerative Scheduling in Concurrent Processing of Frequent Itemset Queries P Boinski, K Jozwiak, M Wojciechowski, M Zakrzewicz Intelligent Information Processing and Web Mining: Proceedings of the …, 2006 | 3 | 2006 |
| Bounding box representation of co-location instances for Chebyshev and Manhattan metrics W Andrzejewski, P Boinski Data & Knowledge Engineering 145, 102153, 2023 | 2 | 2023 |
| Concurrent execution of data mining queries for spatial collocation pattern discovery P Boinski, M Zakrzewicz International Conference on Data Warehousing and Knowledge Discovery, 184-195, 2013 | 2 | 2013 |
Witold AndrzejewskiPoznan University of TechnologyZweryfikowany adres z cs.put.poznan.pl
