The Research Of Recommended Method Of Enterprise Potential R&D Partners Based On Patent

With the increasingly fierce market competition, customer demand is becoming more personalized and diversified. It’s difficult for enterprise to deal with this challenge with their own strength. Therefore, the demand of enterprise is to choose the right R&D partner, in order to achieve competitive advantage. While enterprise often tends to stick to policy maker’s past experience in searching the R&D partners. Patent literature as the main human technical carrier is highly innovative product, condensates the entire human wisdom, bears the forefront of technology information, has the characteristics of high knowledge content. Therefore, this paper uses patent information as data source to recommend potential R&D partners for enterprise with text mining, semantic annotation and TRIZ theory.The main content includes the following three aspects:(1) Extracts function, scientific effect and functional effects of patent related specific technical areas based on TRIZ theory. Builds the field technology tree with patent. Extracts technology areas, technical problems, technical means and technical effect of enterprise specific demand. Recognizes the demand patents with matching scientific effect with TRIZ laws of evolution and technology problems and technical effect in enterprise specific demand. Analyzes the patentee of demand patent sets.(2)Based on previous research of R&D partner selection, this paper takes the patentee information of last step as potential R&D partner, starting from the technical strength of potential R&D partner, the degree of R&D openness and the effect of cooperative R&D, setting indexes which can be calculated on the basis of the patent information, constructing the evaluation system of enterprise potential R&D partners which is based on patent.(3)Chooses the specific needs of enterprises to carry out empirical research, constructing field patent technology tree of related technical fields, extracting key semantic information of enterprise specific needs, using demand patents to recognize algorithm and finish the positioning of demand patents, combined with the evaluation system of enterprise potential R&D partners which is based on patent to finish the evaluation and recommendation of enterprise potential R&D partners.