1, cnki, I have to say that it is the industry leader and has the largest audience. In terms of resources, it covers a wide range, has the advantages of periodicals and doctoral dissertations, and has perfect copyright cooperation, and can basically get all the retrieved ones. If it is not enough, I personally feel that the user experience is average, the page design using the interactive package library is old, and there are few documents provided. And the cost is high.
2. VIP cqvip, which started as a periodical, is still ahead of HowNet in terms of resource breadth and collection time, and the completeness of metadata (bibliographic information) is the highest among the three, so it has obvious advantages in big data application. If it is insufficient, it is still in terms of resources and audiences. Except for periodicals, other resources are a little stretched.
3. wanfang data and Wanfang's revised platform have also made great efforts in data, with good page design, functionality and data presentation. The disadvantage is that the full-text rate is a bit low, with no bright spots and no slots. It seems that the business is shrinking, and the inspection business is not as good as that of VIP.
introduce
After CNKI 1.0 was basically completed, China Knowledge Network fully summarized the experience and lessons of industry knowledge service in the past five years, taking the comprehensive application of big data and artificial intelligence technology to create knowledge innovation service industry as a new starting point, and CNKI project entered the 2.0 era. ?
The goal of CNKI 2.0 is to deepen the knowledge service provided by CNKI 1.0, which is based on the integration of public knowledge with the process and results of knowledge innovation in various industries and institutions, and to provide problem-oriented knowledge service and collaborative research platform to stimulate group wisdom through more accurate, systematic and complete explicit management and tacit knowledge management embedded in specific work and learning processes.