Title :
Semantic Generalization in a Graph-Based Data Model
Author :
Ohira, Yuki ; Hochin, Teruhisa ; Nomiya, Hiroki
Author_Institution :
Grad. Sch. of Inf. Sci., Kyoto Inst. of Technol., Kyoto, Japan
Abstract :
This paper proposes the semantic generalization. This generalization makes it possible for a shape graph, which corresponds to a relation schema in the relational data model, to have elements by considering the semantics of the elements of the original shape graphs even if there is no common element in the original shape graphs. For this purpose, viewpoints and relationship trees are introduced. A viewpoint is a sub graph of a schema graph, and plays a role of a kind of hierarchy of concepts. A relationship tree is a hierarchy of relationships. The semantic generalization is informally and formally described. It is shown that the conventional generalization could be realized by using the semantic generalization.
Keywords :
generalisation (artificial intelligence); graph theory; knowledge representation; graph-based data model; relational data model; relationship trees; semantic generalization; shape graph; Data models; Games; Knowledge engineering; Multimedia communication; Semantics; Shape; Sports equipment; Data model; Generalization; Graph; Semantic Generalization;
Conference_Titel :
Software Engineering, Artificial Intelligence, Networking and Parallel & Distributed Computing (SNPD), 2012 13th ACIS International Conference on
Conference_Location :
Kyoto
Print_ISBN :
978-1-4673-2120-4
DOI :
10.1109/SNPD.2012.77