Method for the Semantic Modelling of the Product Context Using Text Mining for the Derivation of Innovation Potentials
Michael Riesener, Maximilian Kühn, Hendrik Lauf, Günther Schuh · 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM) · 2022
Increased competitive pressure requires companies to increase their own innovative capacity. In particular, innovation management must identify and analyze the external dimensions of influence that affect the product. Although large amounts of text data are available for this purpose, there is yet no possibility of evaluating them in a structured way and linking the information obtained with each other in order to generate knowledge about the product environment. The presented method enables the derivation of innovation potentials from these text data. First, the external dimensions of influence that affect the product and are thus relevant for the innovation process are identified. Each influence dimension also defines data sources that can be used for the analysis. When analyzing the document collection from the data sources, applications from the field of text mining extract the topic areas of the available documents. Finally, a semantic network links the knowledge gained and shows the dependency of the identified topics in order to generate knowledge about future innovation potentials. The method was validated with a use-case from the sports equipment industry.