This paper presents a novel approach to ontology alignment and domain ontology extraction from two existing knowledge bases: WordNet and HowNet. These two knowledge bases are automatically aligned to construct a bilingual ontology based on the co-occurrence of words in a bilingual parallel corpus. The bilingual ontology achieves greater structural and semantic information coverage from these two complementary knowledge bases. For domain-specific applications, a domain-specific ontology is further extracted from the bilingual ontology using the island-driven algorithm and domain-specific corpus. Finally, domain-dependent terminology and axioms between domain terminology defined in a medical
encyclopedia are integrated into the domain-specific ontology. In addition, a metric based on a similarity measure for ontology evaluation is also proposed. For evaluation purposes, experiments were conducted comparing an automatically constructed ontology with a benchmark ontology constructed by ontology engineers or experts. The experimental results show that the constructed bilingual domain-specific ontology mostly coincided with the benchmark ontology. As for application of this approach to the medical domain, the experimental results show that the proposed approach outperformed the synonym expansion approach to web
search.