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% Selection : Author: Daniela_Kurz
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@MastersThesis{Kurz:2000,
      AUTHOR = {Kurz, Daniela},
      TITLE = {Wortstellungspräferenzen im Deutschen},
      YEAR = {2000},
      ADDRESS = {Saarbrücken},
      SCHOOL = {Universität des Saarlandes, Computerlinguistik}
}

@InProceedings{Kurz:2000_1,
      AUTHOR = {Kurz, Daniela},
      TITLE = {A Statistical Account on Word Order Variation in German},
      YEAR = {2000},
      BOOKTITLE = {COLING Workshop on Linguistically Interpreted Corpora (LINC '00), August 6},
      ADDRESS = {Luxembourg},
      URL = {https://www.coli.uni-saarland.de/~kurz/linc00.ps.gz},
      ABSTRACT = {In this paper we present a corpus-based study involving the linear order of subject, indirect object and direct object in German. The aim was to examine several hypotheses derived from Hawkins' (1994) performance theory. In this context it was crucial to examine whether and to which extend length influences the order of subject and objects. The analysis was based on data extracted from the annotated NEGRA corpus (Skut et al., 1998) and the untagged Frankfurter Rundschau corpus. We developed an analysis system operating on the untagged corpus that facilitates the acquisition of data and subsequent statistical analysis. We describe this system and discuss the results drawn from the analysis of the data. These results do not support the theoretical assumptions made by Hawkins. Furthermore, they suggest the investigation of other factors than length.},
      ANNOTE = {COLIURL : Kurz:2000:SAW.pdf Kurz:2000:SAW.ps}
}

@InProceedings{Kurz_et_al:2000,
      AUTHOR = {Kurz, Daniela and Skut, Wojciech and Uszkoreit, Hans},
      TITLE = {German Factors Constraining Word Order Variation},
      YEAR = {2000},
      BOOKTITLE = {13th Annual Conference on Human Sentence Processing, Poster presentation (CUNY 2000), March 30 - April 1},
      ADDRESS = {La Jolla, California, USA},
      NOTE = {poster presentation}
}

@InProceedings{Kurz_Xu:2002,
      AUTHOR = {Kurz, Daniela and Xu, Feiyu},
      TITLE = {Text Mining for the Extraction of Domain Relevant Terms and Term Collocations},
      YEAR = {2002},
      BOOKTITLE = {Proceedings of the International Workshop on Computational Approaches to Collocations},
      ADDRESS = {Vienna},
      URL = {http://www.dfki.de/dfkibib/publications/docs/Kurz_2002_TMEDRTTC.pdf},
      ABSTRACT = {This paper provides a system which combines classification-based term extraction method with the statistical collocation calculations.},
      ANNOTE = {COLIURL : Kurz:2002:TME.pdf}
}

@InProceedings{Xu_et_al:2002,
      AUTHOR = {Xu, Feiyu and Kurz, Daniela and Piskorski, Jakub and Schmeier, Sven},
      TITLE = {Term Extraction and Mining Term Relations from Free-Text Documents in the Financial Domain},
      YEAR = {2002},
      BOOKTITLE = {Proceedings of the 5th International Conference on Business Information Systems (BIS'02), April 24-25},
      ADDRESS = {Poznan, Poland},
      URL = {http://www.dfki.de/~feiyu/Bis2002.pdf},
      ABSTRACT = {In this paper, we present an approach to learning domain relevant terms automatically. We took the financial domain as our experiment domain.},
      NOTE = {to appear},
      ANNOTE = {COLIURL : Xu:2002:TEM.pdf}
}

@InProceedings{Xu_et_al:2002_1,
      AUTHOR = {Xu, Feiyu and Kurz, Daniela and Piskorski, Jakub and Schmeier, Sven},
      TITLE = {A Domain Adaptive Approach to Automatic Acquisition of Domain Relevant Terms and their Relations with Bootstrapping},
      YEAR = {2002},
      BOOKTITLE = {Proceedings of the 3rd International Conference on Language Resources an Evaluation (LREC'02), May 29-31},
      ADDRESS = {Las Palmas, Canary Islands, Spain},
      URL = {http://www.dfki.uni-sb.de/~feiyu/LREC_TermExtraction_final.pdf},
      ABSTRACT = {In this paper, we present an unsupervised hybrid text-mining approach to automatic acquisition of domain relevant terms and their relations. We deploy the TFIDF-based term classification method to acquire domain relevant single-word terms. Further, we apply two strategies in order to learn lexico-syntatic patterns which indicate paradigmatic and domain relevant syntagmatic relations between the extracted terms. The first one uses an existing ontology as initial knowledge for learning lexico-syntactic patterns, while the second is based on different collocation acquisition methods to deal with the free-word order languages like German. This domain-adaptive method yields good results even when trained on relatively small training corpora. It can be applied to different real-world applications, which need domain-relevant ontology, for example, information extraction, information retrieval or text classification.},
      ANNOTE = {COLIURL : Xu:2002:DAA.pdf}
}