Discovering missing background knowledge in ontology matching

Discovering missing background knowledge in ontology matching (2006)

by Fausto Giunchiglia , Fausto Giunchiglia , Pavel Shvaiko , Pavel Shvaiko , Mikalai Yatskevich , Mikalai Yatskevich

Venue:	In Proceedings of ECAI
Citations:	20 - 8 self

Datum	Value	Source
TITLE	Discovering missing background knowledge in ontology matching	INFERENCE
AUTHOR NAME	Fausto Giunchiglia	SVM HeaderParse 0.2
AUTHOR NAME	Fausto Giunchiglia	SVM HeaderParse 0.2
AUTHOR NAME	Pavel Shvaiko	SVM HeaderParse 0.2
AUTHOR NAME	Pavel Shvaiko	SVM HeaderParse 0.2
AUTHOR NAME	Mikalai Yatskevich	SVM HeaderParse 0.2
AUTHOR NAME	Mikalai Yatskevich	SVM HeaderParse 0.2
ABSTRACT	Abstract. Semantic matching determines the mappings between the nodes of two graphs (e.g., ontologies) by computing logical relations (e.g., subsumption) holding among the nodes that correspond semantically to each other. We present an approach to deal with the lack of background knowledge in matching tasks by using semantic matching iteratively. Unlike previous approaches, where the missing axioms are manually declared before the matching starts, we propose a fully automated solution. The benefits of our approach are: (i) saving some of the pre-match efforts, (ii) improving the quality of match via iterations, and (iii) enabling the future reuse of the newly discovered knowledge. We evaluate the implemented system on large real-world test cases, thus, proving empirically the benefits of our approach. 1	SVM HeaderParse 0.2
YEAR	2006	SVM HeaderParse 0.2
VENUE	In Proceedings of ECAI	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	382--386	INFERENCE
VOLUME	141	INFERENCE
TECH	Tech. Rep. DIT-06-005	INFERENCE
CITATIONS	17 found	ParsCit 1.0