Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/39883
Title: Automatically integrating heterogeneous ontologies from structured web pages
Authors: Ye, S. 
Chua, T.-S. 
Keywords: Data models
Data schema
Knowledge models
Ontologies
Semantic matching
Issue Date: 2007
Source: Ye, S.,Chua, T.-S. (2007). Automatically integrating heterogeneous ontologies from structured web pages. International Journal on Semantic Web and Information Systems 3 (2) : 99-114. ScholarBank@NUS Repository.
Abstract: This article presents an automated approach to integrate multiple analogous ontologies extracted from structured web pages into a common ontology. These ontologies from heterogeneous systems exhibit rich diversity in appearances, structures, terminologies and granularities. We design a unified similarity paradigm that can collect the implicit and explicit evidences that exhibit coherences among ontology and instance, semantic and structure, as well as linguistic and syntactic features. The similarity between ontology elements is derived from three aspects such as intension, extension and context, denoted by <INT, EXT, CXT>, where INT and EXT include corresponding weighted contents from their offspring, and CXT is relevant to evidences shown in their ancestors. The similarity in each aspect is calculated by means of their semantic overlapping and syntactic comparability. We develop a top-down matching algorithm based on matching space selection and similarity reuse; the algorithm facilitates less error-prone mappings and lower computational cost. Copyright © 2007, IGI Global.
Source Title: International Journal on Semantic Web and Information Systems
URI: http://scholarbank.nus.edu.sg/handle/10635/39883
ISSN: 15526283
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

54
checked on Dec 8, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.