Title :
A semantic extension model used in vegetable supply chain domain concepts acquisition
Author :
Yue, Jun ; Sun, Wandong ; Li, Daoliang ; Fu, Zetian
Abstract :
This paper proposed a new method to acquire vegetable supply chain domain knowledge from three semantic extension layers. For a single domain concept, qualitative reasoning and quantitative reasoning are used to reach the first semantic extension layer; for more than two domain concepts, Advanced Similarity Measure (ASM) arithmetic is adopted to reach the second semantic extension layer. These two semantic extension layers are achieved internal of vegetable supply chain ontology model. WordNet and Locally Linear Embedding (LLE) arithmetic are adopted to reach the third semantic extension layer, which is achieved external of the ontology model. The experiments have proven the efficiency of this method. The method can be expanded to domain concepts acquisition of other fields.
Keywords :
common-sense reasoning; food products; knowledge acquisition; ontologies (artificial intelligence); supply chain management; WordNet; advanced similarity measure; locally linear embedding arithmetic; qualitative reasoning; quantitative reasoning; semantic extension model; vegetable supply chain domain concepts acquisition; Arithmetic; Cognitive science; Educational institutions; Fuzzy reasoning; Intelligent control; Knowledge acquisition; Laboratories; Ontologies; Resource description framework; Supply chains; Voronoi diagram; WordNet; ontology; resource description framework; semantic reasoning;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4593247