Building a feature taxonomy of the terms extracted from a text collection
Proceedings of the Masters Symposium on Advances in Data Mining, Machine Learning, and Computer Vision : Lviv, Ukraine, November 15-16, 2019, 2566, (2019)Abstract
This position paper presents an approach for feature grouping and taxonomic relationship extraction with the further objective to build a feature taxonomy of a learned ontology. The approach needs to be developed as a part of the OntoElect methodology for domain ontologies refinement. The paper contributes a review of the related work in taxonomic relationships extraction from natural language texts. Within this review, the research gaps and remaining challenges are analyzed. The paper proceeds with outlining the envisioned solution. It presents the approach to this solution starting with the research questions, followed by the initial research hypotheses to be tested. Consequently, the plan of research is presented, including the potential research problems, the rationale to use and re-use existing components, and evaluation plan. Finally, the proposed solution, and the project, are placed in the broader context of the overall OntoElect workflow.