In recent years, although the application of knowledge graph in natural language processing has made some progress, there are still some key problems to be solved, especially the matching query problem in natural language knowledge graph. Since the basic data model of knowledge graph is graph, the matching query problem in natural language knowledge graph is usually transformed into graph matching query problem. However, at present, the traditional graph matching technology applied in knowledge graph consumes too much time and has low query efficiency, which cannot meet the needs of users for large-scale natural language knowledge graph query. Based on the full analysis of the defects of the traditional graph matching technology applied in the knowledge graph, according to the characteristics of the natural language knowledge graph, in order to improve the query efficiency, we propose an accurate matching query method of graph hierarchical topological sequence based on the graph model of knowledge graph. Through experiment analysis, compared with the traditional graph model matching algorithm applied in knowledge graph query, this method can quickly filter the unqualified knowledge graph candidate sets, effectively reduce the number of knowledge graph candidate sets, and make it have more advantages in matching efficiency and time performance. In addition, compared with two algorithms of GIndex and FG-Index, this method has better performance in index construction time, average size of candidate set and average running time of online update.
With the gradual maturity of component oriented software development method, component-based software evolution technology has become hot research in academia and industry. Although many evolution rules are designed, they rarely consider component type-mismatched problem in evolution rules. This has led to evolution rules that often run error in software evolution execution. Hence, focusing on the mismatch problem of component type in software evolution, this paper addresses various evolution rules with condition constrains to support component type matching. First, we use the bigraph theory to model the software architecture and employ bigraph term language to describe the basic component evolution operations. Second, we join type system into the term language and use the type term language to express the condition constraints on position and connection for component evolution rules. These condition constraints can guarantee the type-matched among components that participate in software evolution. Furthermore, we show that the component type-matched still kept during a number of different evolution rules are used in the whole software evolution reaction system. Finally, two cases study of evolution progress of ATM system and tourism information system are presented. Two cases illustrate the effectiveness of our approach.
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