Ontology augmentation: combining semantic web and text resources

Miriam Fernandez; Vanessa Lopez; Enrico Motta; Ziqi Zhang; Victoria Uren

doi:10.1145/1999676.1999680

Ontology augmentation: combining semantic web and text resources

Miriam Fernandez, Vanessa Lopez, Enrico Motta, Ziqi Zhang, Victoria Uren

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

This work investigates the process of selecting, extracting and reorganizing content from Semantic Web information sources, to produce an ontology meeting the specifications of a particular domain and/or task. The process is combined with traditional text-based ontology learning methods to achieve tolerance to knowledge incompleteness. The paper describes the approach and presents experiments in which an ontology was built for a diet evaluation task. Although the example presented concerns the specific case of building a nutritional ontology, the methods employed are domain independent and transferrable to other use cases.

Original language	English
Title of host publication	Proceeding : K-CAP '11
Subtitle of host publication	proceedings of the sixth international conference on knowledge capture
Place of Publication	New York, NY (US)
Publisher	ACM
Pages	9-16
Number of pages	8
ISBN (Print)	978-1-4503-0396-5
DOIs	https://doi.org/10.1145/1999676.1999680
Publication status	Published - 2011
Event	6th International Conference on Knowledge Capture - Alberta, Canada Duration: 25 Jun 2011 → 29 Jun 2011

Conference

Conference	6th International Conference on Knowledge Capture
Abbreviated title	KCAP 2011
Country/Territory	Canada
City	Alberta
Period	25/06/11 → 29/06/11

Access to Document

10.1145/1999676.1999680

Cite this

@inproceedings{b91afdd4426c47199ae7ee245b785f95,

title = "Ontology augmentation: combining semantic web and text resources",

abstract = "This work investigates the process of selecting, extracting and reorganizing content from Semantic Web information sources, to produce an ontology meeting the specifications of a particular domain and/or task. The process is combined with traditional text-based ontology learning methods to achieve tolerance to knowledge incompleteness. The paper describes the approach and presents experiments in which an ontology was built for a diet evaluation task. Although the example presented concerns the specific case of building a nutritional ontology, the methods employed are domain independent and transferrable to other use cases.",

author = "Miriam Fernandez and Vanessa Lopez and Enrico Motta and Ziqi Zhang and Victoria Uren",

year = "2011",

doi = "10.1145/1999676.1999680",

language = "English",

isbn = "978-1-4503-0396-5",

pages = "9--16",

booktitle = "Proceeding : K-CAP '11",

publisher = "ACM",

address = "United States",

note = "6th International Conference on Knowledge Capture, KCAP 2011 ; Conference date: 25-06-2011 Through 29-06-2011",

}

Fernandez, M, Lopez, V, Motta, E, Zhang, Z & Uren, V 2011, Ontology augmentation: combining semantic web and text resources. in Proceeding : K-CAP '11: proceedings of the sixth international conference on knowledge capture . ACM, New York, NY (US) , pp. 9-16, 6th International Conference on Knowledge Capture, Alberta, Canada, 25/06/11. https://doi.org/10.1145/1999676.1999680

TY - GEN

T1 - Ontology augmentation

T2 - 6th International Conference on Knowledge Capture

AU - Fernandez, Miriam

AU - Lopez, Vanessa

AU - Motta, Enrico

AU - Zhang, Ziqi

AU - Uren, Victoria

PY - 2011

Y1 - 2011

N2 - This work investigates the process of selecting, extracting and reorganizing content from Semantic Web information sources, to produce an ontology meeting the specifications of a particular domain and/or task. The process is combined with traditional text-based ontology learning methods to achieve tolerance to knowledge incompleteness. The paper describes the approach and presents experiments in which an ontology was built for a diet evaluation task. Although the example presented concerns the specific case of building a nutritional ontology, the methods employed are domain independent and transferrable to other use cases.

AB - This work investigates the process of selecting, extracting and reorganizing content from Semantic Web information sources, to produce an ontology meeting the specifications of a particular domain and/or task. The process is combined with traditional text-based ontology learning methods to achieve tolerance to knowledge incompleteness. The paper describes the approach and presents experiments in which an ontology was built for a diet evaluation task. Although the example presented concerns the specific case of building a nutritional ontology, the methods employed are domain independent and transferrable to other use cases.

UR - http://www.scopus.com/inward/record.url?scp=79960255541&partnerID=8YFLogxK

UR - http://dl.acm.org/citation.cfm?doid=1999676.1999680

U2 - 10.1145/1999676.1999680

DO - 10.1145/1999676.1999680

M3 - Conference publication

AN - SCOPUS:79960255541

SN - 978-1-4503-0396-5

SP - 9

EP - 16

BT - Proceeding : K-CAP '11

PB - ACM

CY - New York, NY (US)

Y2 - 25 June 2011 through 29 June 2011

ER -

Ontology augmentation: combining semantic web and text resources

Abstract

Conference

Access to Document

Other files and links

Fingerprint

Cite this