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Found 6 papers, 2 papers with code
RetClean: Retrieval-Based Data Cleaning Using Foundation Models and Data Lakes
To assist with this scenario, we developed a custom RoBERTa-based foundation model that can be locally deployed.
Deep learning for blocking in entity matching: a design space exploration
In this paper, we develop the DeepBlocker framework that significantly advances the state of the art in applying DL to blocking for EM.
Ranked #5 on
Blocking
on Abt-Buy
RPT: Relational Pre-trained Transformer Is Almost All You Need towards Democratizing Data Preparation
RPT is pre-trained for a tuple-to-tuple model by corrupting the input tuple and then learning a model to reconstruct the original tuple.
Reuse and Adaptation for Entity Resolution through Transfer Learning
Entity resolution (ER) is one of the fundamental problems in data integration, where machine learning (ML) based classifiers often provide the state-of-the-art results.
DeepER -- Deep Entity Resolution
word embeddings), we present a novel ER system, called DeepER, that achieves good accuracy, high efficiency, as well as ease-of-use (i. e., much less human efforts).
Databases
A large scale study of SVM based methods for abstract screening in systematic reviews
However, it is very hard to clearly understand the applicability of these methods in a systematic review platform because of the following challenges: (1) the use of non-overlapping metrics for the evaluation of the proposed methods, (2) usage of features that are very hard to collect, (3) using a small set of reviews for the evaluation, and (4) no solid statistical testing or equivalence grouping of the methods.
