LinkedCJ: A Knowledge Base of Chinese Academic Journals Based on Linked Data.

Nowadays the amount of academic articles published in Chinese is growing rapidly, however, existing methods of managing and querying Chinese academic journals and articles are not semantic-based. Our work consists of creating an ontology for represents and organizing bibliographic information of Chinese academic journals and articles. Moreover, we develop software applications based on Nutch, jsoup, and Drools for transforming millions of Web pages from website of Wanfang into approximately 15 million triples stored in a triple store. Finally, the knowledge base is evaluated using the Semantic Service Platform of Chinese Academic Journals and Articles (SSPCAJA). Results of the functional test show that information of Chinese academic journals and articles is effectively represented on the platform.