@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}
}
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