In order to solve the semantic irreconcilable problems caused by contextual differences during the process of ontology integration, a context-driven reconciliation mechanism is proposed. The mechanism is based on the ...In order to solve the semantic irreconcilable problems caused by contextual differences during the process of ontology integration, a context-driven reconciliation mechanism is proposed. The mechanism is based on the previous work about a context-based formalism-Context-SHOIQ （D ＋ ） DL, which is used for explicitly representing context of ontology by adopting the description logic and the category theory. The formalism is extended by adding four migration rules （InclusionRule, SelectionRule, PreferenceRule, and MappingRule）, that are used to specify what should be imported into the IntegrativeContext, and three related contextual integration operations of increasing interoperability （import, partial reconciliation, and full reconciliation）. While not exhaustive, the mechanism is sufficient for solving the five types of semantic irreconcilable problems that are discussed, and favors integration of ontologies from one context to another.展开更多
A context memory model and an approach for context query and association discovery are proposed. The context query is based on a resource description framework （RDF） dataset and SPARQL language. To discover collabor...A context memory model and an approach for context query and association discovery are proposed. The context query is based on a resource description framework （RDF） dataset and SPARQL language. To discover collaborative associations, an approach of transforming RDF named graphs into ＂context graph＂ is proposed. First, the definitions of the importance of the nodes and the weight assignment for the ＂context graph＂ are given. Secondly, the implementation of a spread activation algorithm based on ＂context graph＂ is proposed. An infrastructure is also built up in the collaborative context space （CCS） system to support context memory and knowledge discovery in a collaborative environment.展开更多
A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a pr...A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a procedure with the given labels, and then captures the callees＇ influence on callers when analyzing call statements. Phase 2 captures the callees＇ dependence on callers by replacing all given labels appearing in the corresponding sets of formal parameters. By the introduction of given labels, this slice method can obtain similar summary information in system-dependence-graph（SDG）-based algorithms for addressing the calling-context problem. With the use of the slice monad transformer, this monadic slicing approach achieves a high level of modularity and flexibility. It shows that the monadic interprocedural algorithm has less complexity and it is not less precise than SDG algorithms.展开更多
文摘In order to solve the semantic irreconcilable problems caused by contextual differences during the process of ontology integration, a context-driven reconciliation mechanism is proposed. The mechanism is based on the previous work about a context-based formalism-Context-SHOIQ （D ＋ ） DL, which is used for explicitly representing context of ontology by adopting the description logic and the category theory. The formalism is extended by adding four migration rules （InclusionRule, SelectionRule, PreferenceRule, and MappingRule）, that are used to specify what should be imported into the IntegrativeContext, and three related contextual integration operations of increasing interoperability （import, partial reconciliation, and full reconciliation）. While not exhaustive, the mechanism is sufficient for solving the five types of semantic irreconcilable problems that are discussed, and favors integration of ontologies from one context to another.
基金The National Natural Science Foundation of China(No.90412009).
文摘A context memory model and an approach for context query and association discovery are proposed. The context query is based on a resource description framework （RDF） dataset and SPARQL language. To discover collaborative associations, an approach of transforming RDF named graphs into ＂context graph＂ is proposed. First, the definitions of the importance of the nodes and the weight assignment for the ＂context graph＂ are given. Secondly, the implementation of a spread activation algorithm based on ＂context graph＂ is proposed. An infrastructure is also built up in the collaborative context space （CCS） system to support context memory and knowledge discovery in a collaborative environment.
基金The National Outstanding Young Scientist Foundation by NSFC(No.60703086,60503020)
文摘A two-phase monadic approach is presented for monadically slicing programs with procedures. In the monadic slice algorithm for interprocedural programs, phase 1 initializes the slice table of formal parameters in a procedure with the given labels, and then captures the callees＇ influence on callers when analyzing call statements. Phase 2 captures the callees＇ dependence on callers by replacing all given labels appearing in the corresponding sets of formal parameters. By the introduction of given labels, this slice method can obtain similar summary information in system-dependence-graph（SDG）-based algorithms for addressing the calling-context problem. With the use of the slice monad transformer, this monadic slicing approach achieves a high level of modularity and flexibility. It shows that the monadic interprocedural algorithm has less complexity and it is not less precise than SDG algorithms.
