A comparison of two ontology-based semantic annotation frameworks

Faculty / School

Faculty of Computer Sciences (FCS)

Department

Department of Computer Science

Was this content written or created while at IBA?

Yes

Document Type

Conference Paper

Publication Date

10-2010

Conference Name

IFIP International Conference on Artificial Intelligence Applications and Innovations

Conference Location

Larnaca, Cyprus

Conference Dates

6-7 October 2010

ISBN/ISSN

78549255549 (Scopus)

Volume

339

First Page

187

Last Page

194

Publisher

Springer, Berlin, Heidelberg

Abstract / Description

The paper compares two semantic annotation frameworks that are designed for unstructured and ungrammatical domains. Both frameworks, namely ontoX (ontology-driven information Extraction) and BNOSA (Bayesian network and ontology based semantic annotation), extensively use ontologies during knowledge building, rule generation and data extraction phases. Both of them claim to be scalable as they allow a knowledge engineer, using either of these frameworks, to employ them for any other domain by simply plugging the corresponding ontology to the framework. They, however, differ in the ways conflicts are resolved and missing values are predicted. OntoX uses two heuristic measures, named level of evidence and level of confidence, for conflict resolution while the same task is performed by BNOSA with the aid of Bayesian networks. BNOSA also uses Bayesian networks to predict missing values. The paper compares the performance of both BNOSA and ontoX on the same data set and analyzes their strengths and weaknesses.

Citation/Publisher Attribution

Rajput, Q., & Haider, S. (2010, October). A comparison of two ontology-based semantic annotation frameworks. In IFIP International Conference on Artificial Intelligence Applications and Innovations (pp. 187-194). Springer, Berlin, Heidelberg..

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