Industrial product design method using feature expression and multi-view learning in ICN

In order to realize multi-layer semantic integration and innovation of complex product industrial design, promote multi-disciplinary knowledge sharing and coordination, and improve product quality, the hierarchical semantic concept of product industrial design is put forward based on the theories of product semiotics and cognitive semantics. In addition, the hierarchical semantic industrial design process context model is constructed based on complex product development process and information processing theory using the Information Centric Networking (ICN) technology, since ICN architecture can be used to optimize the product quality. In the ICN environment, the scientific semantic expression methods and the artistic semantic expression method of product semantics are also used to extract features and construct the feature expression in the specific design situation. The icon semantic features, indicative semantic features, symbolic semantic features and their relevance of complex products are obtained. Experimental results have been achieved and shown that the proposed method has benefits than the other methods.