Title :
Learning of ontology from the web-table
Author :
Song-il Cha ; Zong-min Ma ; Jing-wei Cheng ; Fu Zhang
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
Table is ubiquitous in web documents. Turning the web-table information into ontology requires automatic approaches. In this paper, we discuss how to learn ontology from web-table. In order to obtain table schemata for learning of ontology, we first present general layout structure of the table, then, we propose ontology extraction method according to the five table group. The learned ontology includes the following relationships: is-a relationships, class-instance relationships, RDF triples, property domains and property ranges.
Keywords :
Internet; document handling; information retrieval; learning (artificial intelligence); ontologies (artificial intelligence); RDF triples; Web documents; Web-table; class-instance relationships; ontology extraction method; ontology learning; property domains; property ranges; table information extraction; table schemata; Correlation; Data mining; Feature extraction; Layout; Ontologies; Printers; Semantics; class; ontology learning; relationship; table information extracting; web-table;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-180-9
DOI :
10.1109/FSKD.2011.6019792
