Discovering new technology opportunities based on patents: Text-mining and F-term analysis

Abstract

Discovering new technology opportunities has long been a significant issue in both practice and academia. Among various approaches to search for opportunities, one of the most frequently used is to identify emerging or vacant technologies from patent documents. In line with it, this study aims to suggest a novel approach for the development of new technology ideas based on the F-term, which classifies patent documents according to the technical attributes of the inventions described within them. Since the technical attributes are analyzed according to various perspectives through the application of the F-term, which generates detailed and systematic information about technologies, the F-term can provide effective guidelines for generating new technology ideas, if utilized well. In the approach, we first choose a target technology for seeking new opportunities. Then, from the text mining results of the F-term data, we identify other technologies with technical attributes similar to the target technology, called reference technologies. The next step is to extract technical attributes that are commonly used in the reference technologies but have not been used in the target technology. Finally, we can obtain new technology ideas by applying these technical attributes to the target technologies. This is one of the earliest attempts to adopt the F-term for patent analysis; the proposed methodology can show how to best take advantage of the F-term and the wealth of available technical information in patents, and also can be useful in the idea-creation process for major and minor innovation.