Using an Ontology Learning System for Trend Analysis and Detection

نویسندگان

  • Gerhard Wohlgenannt
  • Stefan Belk
  • Matyas Karacsonyi
  • Matthias Schett
چکیده

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 resulting 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.

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تاریخ انتشار 2014