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

Volume

3

fYear

2011

fDate

26-28 July 2011

Firstpage

1454

Lastpage

1458

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-61284-180-9

Type

conf

DOI

10.1109/FSKD.2011.6019792

Filename

6019792