Matching XML documents at structural and conceptual level using subtree patterns
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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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Pan, Qi; Hadzic, Fedja; Dillon, Tharam S. (2010)Concept matching is important when heterogeneous data sources are to be merged for the purpose of knowledge sharing. It has many useful applications in areas such as schema matching, ontology matching, scientific knowledge ...
Hadzic, Fedja; Dillon, Tharam S.; Chang, Elizabeth (2007)Matching of heterogeneous knowledge sources is of increasing importance in areas such as scientific knowledge management, e-commerce, enterprise application integration, and many emerging Semantic Web applications. With ...
Hadzic, Fedja; Dillon, Tharam S. (2007)Abstract: Matching of knowledge structures is generally important for scientific knowledge management, e-commerce, enterprise application integration, etc. With the desire of knowledge sharing and reuse in these fields, ...