Knowledge-based systems are essential to software intelligence, which provide the capabilities of problem-solving reasoning. Due to the bottleneck of knowledge acquisition, developing the knowledge-based systems are not easy. In addition, because of the interaction between knowledge-based systems relies heavily on the knowledge representations, different knowledge-based systems may not be able to interact with each other forming the isolated knowledge islands. With the development of the Internet, the massive information collected on Internet becomes a great source of knowledge. However, how to acquire and update knowledge purposefully and automatically from the massive information, how to manage the large amount of knowledge in an orderly manner, and how to use the updated knowledge effectively remain big challenges.
Ruqian Lu, an academician of CAS, proposed the concept of Knowware, to represent a natural development in IT after hardware and software. Concretely, a knowware is a knowledge module that is independent, commercialized, suitable for computer manipulation, and directly usable by a class of software. One of the main features of Knowware is that it is directly related to intelligence: if software is the condensation and crystallization of knowledge, then knowware is the condensation and crystallization of intelligence.
This platform is built for supporting the development and usage of Knowware. The main capabilities of the platform include: (1) A hierarchical knowledge structure for conceptualizing and categorizing the domain knowledge; (2) A series of leading knowledge acquisition techniques, including the ontology-based online concept/relationship extraction methods, the deep learning-based knowledge abstraction approaches. (3) A model-based unified interface to provide knowledge services.
The innovation of these achievement is demonstrated by a series of patents, software copyrights, as well as the research papers in journals, including IJSEKE, IEEE IS, IJAR, Science in China, and international conferences, including IJCAI, AAAI, ACL, and KSEM. This platform won the first prize of 2013 excellent scientific and technological achievements of institutions of higher learning of the Ministry of education.
