37 citations · 77 across the 9 of their papers we have counts for
9 papers
Entity Matching using Large Language Models
Ralph Peeters, Aaron Steiner, Christian Bizer
Entity matching is the task of deciding whether two entity descriptions refer to the same real-world entity. Entity matching is a central step in most data integration pipelines. M…
Column Type Annotation using ChatGPT
Keti Korini, Christian Bizer
Column type annotation is the task of annotating the columns of a relational table with the semantic type of the values contained in each column. Column type annotation is an impor…
Product Information Extraction using ChatGPT
Alexander Brinkmann, Roee Shraga, Reng Chiz Der +1
Structured product data in the form of attribute/value pairs is the foundation of many e-commerce applications such as faceted product search, product comparison, and product recom…
Using ChatGPT for Entity Matching
Ralph Peeters, Christian Bizer
Entity Matching is the task of deciding if two entity descriptions refer to the same real-world entity. State-of-the-art entity matching methods often rely on fine-tuning Transform…
SC-Block: Supervised Contrastive Blocking within Entity Resolution Pipelines
Alexander Brinkmann, Roee Shraga, Christian Bizer
The goal of entity resolution is to identify records in multiple datasets that represent the same real-world entity. However, comparing all records across datasets can be computati…
WDC Products: A Multi-Dimensional Entity Matching Benchmark
Ralph Peeters, Reng Chiz Der, Christian Bizer
The difficulty of an entity matching task depends on a combination of multiple factors such as the amount of corner-case pairs, the fraction of entities in the test set that have n…
Supervised Contrastive Learning for Product Matching
Ralph Peeters, Christian Bizer
Contrastive learning has moved the state of the art for many tasks in computer vision and information retrieval in recent years. This poster is the first work that applies supervis…
Cross-Language Learning for Entity Matching
Ralph Peeters, Christian Bizer
Transformer-based entity matching methods have significantly moved the state of the art for less-structured matching tasks such as matching product offers in e-commerce. In order t…
Learning Expressive Linkage Rules using Genetic Programming
Robert Isele, Christian Bizer
A central problem in data integration and data cleansing is to find entities in different data sources that describe the same real-world object. Many existing methods for identifyi…