Abstract
Entity Resolution (ER) has been extensively studied over the last decade, with a plethora of algorithmic solutions, techniques, and methodologies having been proposed [1]. The individual state-of-the-art ER algorithms are offered through open-source systems, such as Magellan [2] and JedAI [3], which typically implement end-to-end solutions through a sequence of workflow steps. Each workflow step requires its own special configuration and fine tuning, thus turning the creation of complete ER solutions into a non-trivial, time-consuming process that requires adapting, among others, to the characteristics of the data to be resolved (e.g., relational, semi-structured, etc.), to its intrinsic noise (e.g., misspellings, abbreviations, etc.) as well as to application constraints (e.g., execution time).
Original language | English |
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Title of host publication | Proceedings - 2024 IEEE 40th International Conference on Data Engineering, ICDE 2024 |
Publisher | IEEE |
Pages | 5664 |
Number of pages | 1 |
ISBN (Electronic) | 9798350317152 |
ISBN (Print) | 9798350317152 |
DOIs | |
Publication status | Published - 23 Jul 2024 |
Event | 40th IEEE International Conference on Data Engineering, ICDE 2024 - Utrecht, Netherlands Duration: 13 May 2024 → 17 May 2024 |
Publication series
Name | Proceedings - International Conference on Data Engineering |
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ISSN (Print) | 1084-4627 |
ISSN (Electronic) | 2375-0286 |
Conference
Conference | 40th IEEE International Conference on Data Engineering, ICDE 2024 |
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Country/Territory | Netherlands |
City | Utrecht |
Period | 13/05/24 → 17/05/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- entity resolution
- integration