Matching XML documents at structural and conceptual level using subtree patterns

Knowledge matching is an important problem for many emerging applications in many areas including scientific knowledge management, ontology matching, e-commerce, and enterprise application integration. Matching the concepts of heterogeneous knowledge representations is very challenging due to the di...

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Main Authors: Pan, Qi Hua, Hadzic, Fedja, Dillon, Tharam
Other Authors: Andrea Tagarelli
Format: Book Chapter
Published: IGI Global 2011
Online Access:http://hdl.handle.net/20.500.11937/28069
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author Pan, Qi Hua
Hadzic, Fedja
Dillon, Tharam
author2 Andrea Tagarelli
author_facet Andrea Tagarelli
Pan, Qi Hua
Hadzic, Fedja
Dillon, Tharam
author_sort Pan, Qi Hua
building Curtin Institutional Repository
collection Online Access
description Knowledge matching is an important problem for many emerging applications in many areas including scientific knowledge management, ontology matching, e-commerce, and enterprise application integration. Matching the concepts of heterogeneous knowledge representations is very challenging due to the difficulty of taking contextual information into account and detecting complex matches. In this chapter, we describe a knowledge matching approach that uses subtree patterns to utilize structural information for matching at the conceptual and structural level. Initially, the algorithm does not take any syntactic information into account, but rather forms candidate mappings according to their structural/contextual relationships in the knowledge structures, which are then validated using online dictionaries and string similarity measures. The approach will then automatically extract the knowledge structure that is shared among all the matched knowledge representations. Experimental evaluation is performed on a number of real world XML schemas, which demonstrates the effectiveness of the proposed approach.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-280692017-01-30T13:02:56Z Matching XML documents at structural and conceptual level using subtree patterns Pan, Qi Hua Hadzic, Fedja Dillon, Tharam Andrea Tagarelli Knowledge matching is an important problem for many emerging applications in many areas including scientific knowledge management, ontology matching, e-commerce, and enterprise application integration. Matching the concepts of heterogeneous knowledge representations is very challenging due to the difficulty of taking contextual information into account and detecting complex matches. In this chapter, we describe a knowledge matching approach that uses subtree patterns to utilize structural information for matching at the conceptual and structural level. Initially, the algorithm does not take any syntactic information into account, but rather forms candidate mappings according to their structural/contextual relationships in the knowledge structures, which are then validated using online dictionaries and string similarity measures. The approach will then automatically extract the knowledge structure that is shared among all the matched knowledge representations. Experimental evaluation is performed on a number of real world XML schemas, which demonstrates the effectiveness of the proposed approach. 2011 Book Chapter http://hdl.handle.net/20.500.11937/28069 IGI Global restricted
spellingShingle Pan, Qi Hua
Hadzic, Fedja
Dillon, Tharam
Matching XML documents at structural and conceptual level using subtree patterns
title Matching XML documents at structural and conceptual level using subtree patterns
title_full Matching XML documents at structural and conceptual level using subtree patterns
title_fullStr Matching XML documents at structural and conceptual level using subtree patterns
title_full_unstemmed Matching XML documents at structural and conceptual level using subtree patterns
title_short Matching XML documents at structural and conceptual level using subtree patterns
title_sort matching xml documents at structural and conceptual level using subtree patterns
url http://hdl.handle.net/20.500.11937/28069