Exploring Document Collections with Topic Frames
Alexander Hinneburg, F. Rosner, Stefan Peßler, Christian Oberländer · 2014
Topics automatically derived by topic models are not always easy and clearly interpretable by humans. The most probable top words of a topic may leave room for ambiguous interpretations, especially when the top words are exclusively nouns. We demonstrate how part-of-speech (POS) tagging and co-location analysis of terms can be used to derive linguistic frames that yield more interpretable topic representations. The so-called topic frames are demonstrated as feature of the TopicExplorer system that allows to explore document collections using topic models, visualizations and key word search. Demo versions of TopicExplorer are available at http://topicexplorer.informatik.uni-halle.de/ .