Fuzzy Ontology Support for Knowledge Mobilisation

Classical management science is making the transition to analytics, which has the same agenda to support managerial planning, problem solving and decision making in industrial and business contexts but is combining the classical models and algorithms with modern, advanced technology for handling data, information and knowledge. We run a knowledge mobilisation project as a joint effort by Institute for Advanced Management Systems Research, and VTT Technical Research Centre of Finland. The goal was to mobilise knowledge stored in heterogeneous databases for users with various backgrounds, geographical locations and situations. The working hypothesis of the project was that fuzzy mathematics combined with domain-specific data models, in other words, fuzzy ontologies, would help manage the uncertainty in finding information that matches the users’ needs. In this paper, we describe an industrial application of fuzzy ontologies in information retrieval for a paper machine where problem-solving reports are annotated with keywords and then stored in a database for later use. One of the key insights turned out to be that using the Bellmann-Zadeh principles for fuzzy decision-making are useful for identifying keyword dependencies in a keyword taxonomic tree.