Paper Info
Title
The Chinese Conceptual Graph Matching Algorithm Based on Conceptual Sub-graph Weight Self-Adjustment
Abstract
Semantic computing is an important task in the research of natural language processing. For the problem of the inaccurate conceptual graph matching, this paper proposed the algorithm based on Conceptual sub-Graph weight self-adjustment. Based on the in tensional logic model of Chinese concept connotation, using Recursive Conceptual Graph as knowledge representation method and combining with the computation method of E-A-V structures similarity, the algorithm computed the similarity of conceptual graphs. When using this algorithm to compute the Conceptual Graph similarity, it can give the homologous weight to the sub graph based on the proportion of how much information the sub graph contains in the whole Conceptual Graph. The experiment results show that this new algorithm achieve better results.
Year
DOI
Venue
2014
10.1109/3PGCIC.2014.59
3PGCIC
Keywords
Field
DocType
chinese concept connotation,knowledge representation method,conceptual graph similarity,chinese conceptual graph matching algorithm,chinese semantic analysis,semantic computing,conceptual graph,chinese semantic analysis, conceptual graph, e-a-v concept structures similarity, conceptual sub-graph weight self-adjustment,pattern matching,knowledge representation,tensional logic model,recursive conceptual graph,e-a-v structure similarity computation method,graph theory,natural language processing,e-a-v concept structures similarity,conceptual sub-graph weight self-adjustment,mathematical model,algorithm design and analysis,semantics,computational modeling
Graph database,Algorithm design,Conceptual graph,Theoretical computer science,Graph rewriting,Clique-width,Blossom algorithm,Graph (abstract data type),Mathematics,Moral graph
Conference
Citations 
PageRank 
References 
0
0.34
2
Authors
3
Name
Order
Citations
PageRank
Hui Zeng100.68
Liyan Xiong200.68
Jianjun Chen33912.52