Daniela Kurz

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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(More)
In this paper, we present an unsupervised hybrid textmining approach to automatic acquisition of domain relevant terms and their relations. We deploy the TFIDFbased term classification method to acquire domain relevant terms. Further, we apply two strategies in order to learn lexico-syntatic patterns which indicate paradigmatic and domain relevant(More)
In this paper we present an algorithm to anchor floating quantifiers in Japanese, a language in which quantificational nouns and numeralclassifier combinations can appear separated from the noun phrase they quantify. The algorithm differentiates degree and event modifiers from nouns that quantify noun phrases. It then finds a suitable anchor for such(More)
In this paper we present an algorithm to anchor floating quantifiers in Japanese, a language in which quantificational nouns and numeralclassifier combinations can appear separated from the noun phrase they quantify. The algorithm differentiates degree and event modifiers from nouns that quantify noun phrases. It then finds a suitable anchor for such(More)
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