An XML query rewriting mechanism with multiple ontologies integration based on complex semantic mapping

Gu, Jinguang; Xu, Bin; Chen, Xinmeng

doi:10.1016/j.inffus.2007.04.002

Cited by 18 publications

(9 citation statements)

References 10 publications

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“…From the view of information integration, all the local information sites can be expressed as the collections of database enabled information systems (DISs), which means it can support structural query interface. By an database enabled information system we mean S = ({I d }, W ), where {I d } is a finite set of database instances, W is the ontology based wrapper or mediator [4]. In this paper, we employ ontology to define semantic wrappers or mediators, which are used for the explicit description of the information source semantics.…”

Section: Semantic Enabled Distributed Database Systemsmentioning

confidence: 99%

“…Decomposition mapping is used to map a combined concept to one local concept, and the example for the decomposition mapping is the reverse of the composition. These four mapping patterns was discussed in paper [4] This paper defines some properties of semantic mapping which are useful in the task of semantic query planning. The first property is transitivity, for the mapping…”

Section: Semantic Fusion Based On the Patternsmentioning

confidence: 99%

“…From above description, we know that this paper employs the GAV(Global as View) method to process the user's query [1]. The knowledge stored at mediator supply a global seman- tic view of the wrappers, which can be described as the ontology fusion connections list, and it can be described as [4]: As has been mentioned above, the mapping patterns are direct mapping, subsumption mapping and composition mapping, the fusion connection can be described as F cd , F cs and F cc respectively. The query can be described as a structural query with semantic enhanced, which can be described as an extension of relational algebra.…”

Section: Semantic Query Rewriting and Planningmentioning

confidence: 99%

“…Section 5 discusses ontology enabled querying rewriting and planning. Section 6 introduce a prototype system named OBSA [4] which employed the technology discussed in this paper. Section 7 summarizes the whole paper.…”

Section: Introductionmentioning

confidence: 99%

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Heterogeneous Database Semantic Integration Based on Ontology

Chen¹,

Chen

He³

et al. 2008

IJIES

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To enable accessing deep web information at semantic level, this paper develops a semantic query rewriting and planning mechanism on heterogeneous database enabled web information system with complex ontology mapping technology. It discusses the procedure of converting database schema and instances to ontologies at first, and then the patterns of complex ontology mappings , and then the ontology-based query planning in Mediator-Wrapper based environment with GAV style querying request. The relational algebra rewriting and planning algorithm is discussed in detail.

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Section: Semantic Enabled Distributed Database Systemsmentioning

confidence: 99%

Section: Semantic Fusion Based On the Patternsmentioning

confidence: 99%

Section: Semantic Query Rewriting and Planningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Heterogeneous Database Semantic Integration Based on Ontology

Chen¹,

Chen

He³

et al. 2008

IJIES

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“…Semantics is the key to ensure that several information and knowledge sources come to the same meaning of the situation and information/knowledge being communicated. This explains the fact that ontologies support most efforts on KF (e.g., [7][8][9][10][11]). In this chapter a mechanism to ontology-based resource modeling is proposed to overcome resource heterogeneity.…”

Section: Introductionmentioning

confidence: 99%

Knowledge Fusion in Context-Aware Decision Support: Ontology-Based Modeling and Patterns

Smirnov

Levashova

Shilov

et al. 2014

Studies in Fuzziness and Soft Computing

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The purpose of this chapter is twofold: (1) introducing of a semantic modeling mechanism, which is applied to achieve context-based knowledge fusion in a decision support system and (2) discovery of context-based knowledge fusion patterns. An approach to ontology-based resource modeling is proposed. The set of resources comprises sources of data/information/knowledge, problem solving resources and various actors. The knowledge fusion patterns are generalized with regard to two aspects: (1) preserving internal structures of multiple sources from which information/knowledge is fused within the ontological structure of context and preserving internal structure of the context itself, and (2) preserving autonomies of the multiple sources and the context. Six knowledge fusion patterns have been discovered. They are simple fusion, inferred fusion, instantiated fusion, adapted fusion, flat fusion, and historical fusion.

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