Schema and constraints-based matching and merging of topic maps

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Schema and constraints-based matching and merging of topic maps
Authors: Jung-Mn Kim, Hyopil Shin, Hyoung-Joo Kim [edit item]
Citation: Information Processing and Management 43 (4): 930-945. 2007.
Publication type: Journal article
Peer-reviewed: Yes
Database(s):
DOI: 10.1016/j.ipm.2006.08.012.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
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Schema and constraints-based matching and merging of topic maps is a publication by Jung-Mn Kim, Hyopil Shin, Hyoung-Joo Kim.


[edit] Abstract

In this paper, we propose a multi-strategic matching and merging approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the Topic Maps. Our multi-strategic matching approach consists of a linguistic module and a Topic Map constraints-based module. A linguistic module computes similarities between concepts using morphological analysis, string normalization and tokenization and language-dependent heuristics. A Topic Map constraints-based module takes advantage of several Topic Maps-dependent techniques such as a topic property-based matching, a hierarchy-based matching, and an association-based matching. This is a composite matching procedure and need not generate a cross-pair of all topics from the ontologies because unmatched pairs of topics can be removed by characteristics and constraints of the Topic Maps. Merging between Topic Maps follows the matching operations. We set up the MERGE function to integrate two Topic Maps into a new Topic Map, which satisfies such merge requirements as entity preservation, property preservation, relation preservation, and conflict resolution. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Wikipedia philosophy ontology as input ontologies. Our experiments show that the automatically generated matching results conform to the outputs generated manually by domain experts and can be of great benefit to the following merging operations.

[edit] Research questions

"In this paper, we propose a multi-strategic matching and merging approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the Topic Maps."

Research details

Topics: Ontology building [edit item]
Domains: Linguistics [edit item]
Theory type: Design and action [edit item]
Wikipedia coverage: Sample data [edit item]
Theories: "earlier approaches convert ontologies or schemas of relational database, object oriented database, and XML, into a graph model with only nodes and edges for supporting different applications and multiple schema types (Bouquet et al., 2003 and Giunchglia and Shvaiko, 2003).

Topic Maps Reference Model (Durusau, Newcomb, & Barta, 2006) defines a generic merging function based on the equivalence rules to determine if two or more topic items can be merged. The equivalence rules include topic items, topic name item, variant name, occurrence item, association items, and association role item equivalence conditions." [edit item]

Research design: Experiment, Statistical analysis [edit item]
Data source: Experiment responses, Websites [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: User [edit item]
Wikipedia data extraction: Live Wikipedia [edit item]
Wikipedia page type: Article [edit item]
Wikipedia language: Not specified [edit item]

[edit] Conclusion

"Our experiments show that the automatically generated matching results conform to the outputs generated manually by domain experts and can be of great benefit to the following merging operations."

[edit] Comments


Further notes[edit]

Facts about "Schema and constraints-based matching and merging of topic maps"RDF feed
AbstractIn this paper, we propose a multi-strategiIn this paper, we propose a multi-strategic matching and merging approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the Topic Maps. Our multi-strategic matching approach consists of a linguistic module and a Topic Map constraints-based module. A linguistic module computes similarities between concepts using morphological analysis, string normalization and tokenization and language-dependent heuristics. A Topic Map constraints-based module takes advantage of several Topic Maps-dependent techniques such as a topic property-based matching, a hierarchy-based matching, and an association-based matching. This is a composite matching procedure and need not generate a cross-pair of all topics from the ontologies because unmatched pairs of topics can be removed by characteristics and constraints of the Topic Maps. Merging between Topic Maps follows the matching operations. We set up the MERGE function to integrate two Topic Maps into a new Topic Map, which satisfies such merge requirements as entity preservation, property preservation, relation preservation, and conflict resolution. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Wikipedia philosophy ontology as input ontologies. Our experiments show that the automatically generated matching results conform to the outputs generated manually by domain experts and can be of great benefit to the following merging operations.nefit to the following merging operations.
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
ConclusionOur experiments show that the automatically generated matching results conform to the outputs generated manually by domain experts and can be of great benefit to the following merging operations.
Data sourceExperiment responses + and Websites +
Doi10.1016/j.ipm.2006.08.012 +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22Schema%2Band%2Bconstraints-based%2Bmatching%2Band%2Bmerging%2Bof%2Btopic%2Bmaps%22 +
Has authorJung-Mn Kim +, Hyopil Shin + and Hyoung-Joo Kim +
Has domainLinguistics +
Has topicOntology building +
Issue4 +
Pages930-945 +
Peer reviewedYes +
Publication typeJournal article +
Published inInformation Processing and Management +
Research designExperiment + and Statistical analysis +
Research questionsIn this paper, we propose a multi-strategic matching and merging approach to find correspondences between ontologies based on the syntactic or semantic characteristics and constraints of the Topic Maps.
Revid10,933 +
Theoriesearlier approaches convert ontologies or searlier approaches convert ontologies or schemas of relational database, object oriented database, and XML, into a graph model with only nodes and edges for supporting different applications and multiple schema types (Bouquet et al., 2003 and Giunchglia and Shvaiko, 2003). Topic Maps Reference Model (Durusau, Newcomb, & Barta, 2006) defines a generic merging function based on the equivalence rules to determine if two or more topic items can be merged. The equivalence rules include topic items, topic name item, variant name, occurrence item, association items, and association role item equivalence conditions.ociation role item equivalence conditions.
Theory typeDesign and action +
TitleSchema and constraints-based matching and merging of topic maps
Unit of analysisUser +
Urlhttp://dx.doi.org/10.1016/j.ipm.2006.08.012 +
Volume43 +
Wikipedia coverageSample data +
Wikipedia data extractionLive Wikipedia +
Wikipedia languageNot specified +
Wikipedia page typeArticle +
Year2007 +