Ten Challenges for Ontology Matching

By Pavel Shvaiko, Jérôme Euzenat. 2008

351 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems, Knowledge Graphs & Representation

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

1. Pavel Shvaiko
2. Jérôme Euzenat
3. Simon Lacoste-Julien
4. Cássia Trojahn dos Santos
5. Heiner Stuckenschmidt
6. Christian Meilicke
7. Zoubin Ghahramani
8. Yoshua Bengio

In Computer Networks and Communications

1. Pavel Shvaiko
2. Jérôme Euzenat
3. Heiner Stuckenschmidt
4. Cássia Trojahn dos Santos
5. Christian Meilicke
6. Simon Lacoste-Julien
7. Alex Davies
8. Gjergji Kasneci

In Information Systems

1. Pavel Shvaiko
2. Jérôme Euzenat
3. Cássia Trojahn dos Santos
4. Heiner Stuckenschmidt
5. Christian Meilicke
6. Zoubin Ghahramani
7. Simon Lacoste-Julien
8. Alex Davies

In Knowledge Graphs & Representation

1. Jérôme Euzenat
2. Pavel Shvaiko
3. Simon Lacoste-Julien
4. Alex Davies
5. Gjergji Kasneci
6. Thore Graepel
7. Zoubin Ghahramani
8. Konstantina Palla

Citations in the corpus

• SIGMa: simple greedy matching for aligning large knowledge bases (2012, background): “[26] P. Shvaiko and J. Euzenat.”
• Ontology Matching: State of the Art and Future Challenges (2013, neutral): “Finally, Section 15 provides the major conclusions.”
• Ontology Alignment Evaluation Initiative: Six Years of Experience (2011, background): “The work in [60] described ten challenges for ontology matching.”
• Processing (2020, neutral): “For any extended practice experience, it is important to determine whether gains observed in microcomputer performances carry over to other and more traditional classroom media.”