Dec 31, 2023 · To address this issue, we propose a new methodology for yielding benchmark datasets. We put it into practice by creating four new matching tasks ...
A Critical Re-evaluation of Record Linkage Benchmarks for Learning ...
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In this paper, we aim to cover the above gap by proposing aprincipled framework for assessing the quality of benchmarkdatasets for learning-based matching ...
Bibliographic details on A Critical Re-evaluation of Record Linkage Benchmarks for Learning-Based Matching Algorithms.
Jul 3, 2023 · To address this issue, we propose a new methodology for yielding benchmark datasets. We put it into practice by creating four new matching tasks ...
A Critical Re-evaluation of Record Linkage Bench- marks for Learning-Based Matching Algorithms. George Papadakis. National & Kapodistrian University of Athens ...
The goal of ER is to identify duplicates, i.e., different records that describe the same real-world entities. To this end, an ER matching algorithm receives as ...
A Critical Re-evaluation of Benchmark Datasets for (Deep) Learning-Based Matching Algorithms ... Temporal graph-based clustering for historical record linkage.
To address this issue, we propose a new methodology for yielding benchmark datasets. We put it into practice by creating four new matching tasks, and we verify ...
Our results indicate that Paris, the state-of-the-art non-neural method, statistically significantly outperforms all the representative state-of-the-art neural ...
A Critical Re-evaluation of Benchmark Datasets for (Deep) Learning-Based Matching Algorithms ... A Critical Re-evaluation of Neural Methods for Entity Alignment.