Title :
Auto-acquisition method for fine-grained semantic relations of commodity
Author :
Fu, Kui ; Wu, Yalin ; Liu, Lili ; Chen, Donglin
Author_Institution :
Dept. of Electron. Bus., Wuhan Univ. of Technol., Wuhan, China
Abstract :
To solve the problem of coarse-grained ontology model and lack of fine-grained semantic relations for commodity in application of electronic commerce, this paper proposes an idea of extracting classification feature from the vocabularies of product´s candidate properties, and an automatic acquisition method for fine-grained semantic relations based on supervised learning. According to the practical data, the correct classification rate of commodity reaches 86.05%, its average accuracy also reaches 83.9%, which turns out the effectiveness and feasibility of the proposed approach.
Keywords :
commodity trading; electronic commerce; learning (artificial intelligence); pattern classification; auto-acquisition method; automatic acquisition method; classification feature extraction; commodity; electronic commerce; fine-grained semantic relations; supervised learning; Accuracy; Classification algorithms; Feature extraction; Ontologies; Portable computers; Semantics; Vocabulary; classification features; fine-grained; semantic relation; supervised learning;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
DOI :
10.1109/FSKD.2012.6234011