Generic schema matching, ten years later
By Philip A. Bernstein, Jayant Madhavan, Erhard Rahm. Proceedings of the VLDB Endowment, 2011
318 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/55c186046feee5614cd15909dfcc587e0ff662d8
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Pavel Shvaiko
- Jérôme Euzenat
- Kaushik Chakrabarti
- Surajit Chaudhuri
- Kris Ganjam
- Mohamed Yakout
- Steven Euijong Whang
- Cássia Trojahn dos Santos
In Computer Networks and Communications
- Pavel Shvaiko
- Jérôme Euzenat
- Kaushik Chakrabarti
- Surajit Chaudhuri
- Kris Ganjam
- Mohamed Yakout
- Peter Christen
- Heiner Stuckenschmidt
In Information Systems
- Pavel Shvaiko
- Jérôme Euzenat
- Kaushik Chakrabarti
- Surajit Chaudhuri
- Kris Ganjam
- Mohamed Yakout
- Ping Li
- Anshumali Shrivastava
Citations in the corpus
- InfoGather: entity augmentation and attribute discovery by holistic matching with web tables (2012, background): “Our work on building the SMW graph is related to the vast body of work on schema matching [18, 3, 2].”
- Ontology Matching: State of the Art and Future Challenges (2013, methodology): “Overcoming semantic heterogeneity is typically achieved in two steps, namely: ( i ) matching entities to determine an alignment, i.e., a set of correspondences, and ( ii ) interpreting an alignment according to application needs, such as data translation or query answering.”