Using an ontology learning system for trend analysis and detection
Gerhard Wohlgenannt, Stefan Belk, Matyas Karacsonyi, Matthias Schett · 2014
Abstract. The aim of ontology learning is to generate domain models (semi-) automatically. We apply an ontology learning system to create domain ontologies from scratch in a monthly interval and use the re-sulting data to detect and analyze trends in the domain. In contrast to traditional trend analysis on the level of single terms, the application of semantic technologies allows for a more abstract and integrated view of the domain. A Web frontend displays the resulting ontologies, and a number of analyses are performed on the data collected. This frontend can be used to detect trends and evolution in a domain, and dissect them on an aggregated, as well as a fine-grained-level.