Taxonomy Mining from a Smart City CMS using the Multidimensional Knowledge Representation Approach
Johannes Zenkert, Madjid Fathi · 2024
Taxonomy mining plays an important role for organizing and structuring of data in Content Management Systems (CMS). In this paper, we propose a novel approach that leverages multidimensional knowledge representation (MKR) for taxonomy mining from text documents and enriching the extracted information via Large Language Model (LLM). The data originates from a Smart City project in Germany, which addresses housing, care and health for elderly people. The applied method involves the extraction of relevant keywords from text and the utilization of the MKR framework to analyze and represent the information. Results are provided for a context builder that utilizes GPT-4 to enrich the taxonomy. The enriched taxonomy is then used in a WordPress CMS for information search, structuring and tagging of the blog entries accordingly.