Ontology management for large-scale e-commerce applications

Lee, J.; Goodwin, Richard

doi:10.1109/deec.2005.14

Cited by 11 publications

(2 citation statements)

References 4 publications

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“…As previously mentioned, Motik et al [22] offload integrity constraint checking to the database, further bridging the gap. Finally, other recent works have explored the use of database triggers in the context of ontologies for truth maintenance [9], for transforming axioms into rules [31], and for managing large-scale applications [20].…”

Section: Related Workmentioning

confidence: 99%

Detecting Inconsistencies in the Gene Ontology Using Ontology Databases with Not-gadgets

LePendu

Dou

Howe

2009

On the Move to Meaningful Internet Systems: OTM 2009

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Abstract. We present ontology databases with not-gadgets, a method for detecting inconsistencies in an ontology with large numbers of annotated instances by using triggers and exclusion dependencies in a unique way. What makes this work relevant is the use of the database itself, rather than an external reasoner, to detect logical inconsistencies given large numbers of annotated instances. What distinguishes this work is the use of event-driven triggers together with the introduction of explicit negations. We applied this approach toward the serotonin example, an open problem in biomedical informatics which aims to use annotations to help identify inconsistencies in the Gene Ontology. We discovered 75 inconsistencies that have important implications in biology, which include: (1) methods for refining transfer rules used for inferring electronic annotations, and (2) highlighting possible biological differences across species worth investigating.

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Section: Related Workmentioning

confidence: 99%

Detecting Inconsistencies in the Gene Ontology Using Ontology Databases with Not-gadgets

LePendu

Dou

Howe

2009

On the Move to Meaningful Internet Systems: OTM 2009

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“…Therefore, effective methods for managing, maintaining and processing the large size of Semantic Web data have become more and more important. Research for storing large Semantic Web data written in RDF or OWL to traditional DBMS has already studied [2,3,13]. However, currently most RDF and OWL data are written in the form of RDF/XML, an XML representation for RDF and OWL data, and stored in the traditional file systems.…”

Section: Introductionmentioning

confidence: 99%

Web document compaction by compressing URI references in RDF and OWL data

Lee

Son

Kim

et al. 2008

Proceedings of the 2nd International Conference on Ubiquitous Information Management and Communication

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The enormous web documents in WWW have made it dramatically difficult to retrieve meaningful information which we really want to find out. The Semantic Web technology has been considered to solve the problem and RDF and OWL have emerged as standards for the Semantic Web documents by W3C. The RDF/XML, an XML representation of RDF and OWL, documents are very large as compared to their intrinsic data size because of their inherent verbosity from XML. These large-size RDF/XML documents are inefficient in data exchanging and archiving. In this paper, we propose an efficient method for compressing URI references which may cover very large portions of RDF/XML documents. Our compression method compresses URI references using two-level dictionary-based encoding: one for compressing URI parts of URI references and the other for compressing whole URI references. The performance evaluation using real RDF/XML documents shows that our compression method significantly reduces the size of the RDF/XML documents.

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PROMOD: A Modeling Tool for Product Ontology

Kim

Tark

Lee

et al. 2006

Data Engineering Issues in E-Commerce and Services

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Abstract. Product ontology is often constructed by explicating the domain ontology in a formal ontology language. The OWL Web Ontology Language has been positioned as a standard language. It requires technical expertise to directly represent the domain in OWL. An alternative way is to let a domain expert provide a conceptual representation of the domain, and to mechanically translate it into the corresponding OWL codes. We have developed a modeling tool called PROMOD to achieve this process in the product domain. We employ an Extended Entity-Relationship for conceptual model, enriched with modeling elements specialized for the product domain. We present how each element may be technically represented in OWL. We also provide a modeling scenario to demonstrate the practical feasibility of the tool in the field.

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Ontology management for large-scale e-commerce applications

Cited by 11 publications

References 4 publications

Detecting Inconsistencies in the Gene Ontology Using Ontology Databases with Not-gadgets

Detecting Inconsistencies in the Gene Ontology Using Ontology Databases with Not-gadgets

Web document compaction by compressing URI references in RDF and OWL data

PROMOD: A Modeling Tool for Product Ontology

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