Frameworks for entity matching: A comparison

By Hanna Köpcke, Erhard Rahm. Data & Knowledge Engineering, 2010

427 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Corleone: hands-off crowdsourcing for entity matching (2014, neutral): “, [2, 5, 15, 7]).”
Data Matching (2012, background): “On the other hand, while many different classification techniques have been explored within the domain of data matching, only a few publications have comparatively evaluated several techniques [59, 102, 168].”
Ontology Matching (2007, background): “Indeed, data interlinking is an important task for linked data (Köpcke and Rahm 2010; Ferrara et al. 2011b), so many algorithms have been recently developed.”
Knowledge Graphs (2020, neutral): “[296].”
QuERy: A Framework for Integrating Entity Resolution with Query Processing (2015, background): “A thorough overview of the existing work in this area can be found in surveys [11, 20].”
Entity Linking with a Knowledge Base: Issues, Techniques, and Solutions (2015, background): “Another related problem is record linkage [34,35,36, 37,38,39,40,41] (also called duplicate detection, entity matching, and reference reconciliation) in the database community.”
Evaluation of entity resolution approaches on real-world match problems (2010, background): “their evaluation of entity resolution approaches(1) and provide an overview of selected studies in our recent survey paper [20].”
LINDA: distributed web-of-data-scale entity matching (2012, background): “Classical record linkage typically relies on similarity measures between strings and between records [8, 1].”