Auto-acquisition method for fine-grained semantic relations of commodity
Kui Fu, Yalin Wu, Lili Liu, Donglin Chen · 2012
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.