This comparison evaluates the exploitation of unstructured data in industrial quality analysis methods. It shows that textual resources provides tremendously more and more detailed information for some tasks than established data mining methods on structured data.
Hänig, C., Schierle, M. und Trabold, D.: Comparison of Structured vs. Unstructured Data for Industrial Quality Analysis. In: Proceedings of the World Congress on Engineering and Computer Science 2010 Vol I (WCECS 2010), IAENG, 2010
(Best Paper Award)
In this study, we investigated differences between “heavy” (“take a computer”) and “light” verbs (“take a shower”).
Brain Research, Volume 1249, 16 January 2009, Pages 173–180
This work extends our previous unsupervised parsing model by head detection and phrase type clustering and significantly improves the capability to parse sentences without labelled training data.
Hänig, C.: Improvements in Unsupervised Co-Occurrence Based Parsing. In: Proceedings of the Fourteenth Conference on Computational Natural Language Learning (CoNLL 2010), Association for Computational Linguistics, 2010