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- 558 isPartOf proceedings.
- 558 keyword "Acquisition, Machine Learning".
- 558 keyword "Corpus (creation, annotation, etc.)".
- 558 keyword "Information Extraction, Information Retrieval".
- 558 title "Relationships between Nursing Converstaions and Activities".
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- item-1 hasContent hiromi-itoh-ozaku.
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- 559 creator charlotte-giesbers.
- 559 creator folkert-de-vriend.
- 559 creator jan-pieter-kunst.
- 559 creator louis-ten-bosch.
- 559 creator roeland-van-hout.
- 559 type InProceedings.
- 559 label "Evaluating the Relationship between Linguistic and Geographic Distances using a 3D Visualization".
- 559 sameAs 559.
- 559 abstract "In this paper we discuss how linguistic and geographic distances can be related using a 3D visualization. We will convert linguistic data for locations along the German-Dutch border to linguistic distances that can be compared directly to geographic distances. This enables us to visualize linguistic distances as real distances with the use of the third dimension available in 3D modelling software. With such a visualization we will test if descriptive dialect data support the hypothesis that the German-Dutch state border became a linguistic border between the German and Dutch dialects. Our visualization is implemented in the 3D modelling software SketchUp.".
- 559 hasAuthorList authorList.
- 559 hasTopic Linguistics.
- 559 isPartOf proceedings.
- 559 keyword "Endangered languages".
- 559 keyword "Lexicon, lexical database".
- 559 keyword "Tools, systems, applications".
- 559 title "Evaluating the Relationship between Linguistic and Geographic Distances using a 3D Visualization".
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- item-1 hasContent folkert-de-vriend.
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- 56 creator alexandru-ceausu.
- 56 creator dan-tufis.
- 56 creator elena-irimia.
- 56 creator radu-ion.
- 56 type InProceedings.
- 56 label "Unsupervised Lexical Acquisition for Part of Speech Tagging".
- 56 sameAs 56.
- 56 abstract "It is known that POS tagging is not very accurate for unknown words (words which the POS tagger has not seen in the training corpora). Thus, a first step to improve the tagging accuracy would be to extend the coverage of the tagger s learned lexicon. It turns out that, through the use of a simple procedure, one can extend this lexicon without using additional, hard to obtain, hand-validated training corpora. The basic idea consists of merely adding new words along with their (correct) POS tags to the lexicon and trying to estimate the lexical distribution of these words according to similar ambiguity classes already present in the lexicon. We present a method of automatically acquire high quality POS tagging lexicons based on morphologic analysis and generation. Currently, this procedure works on Romanian for which we have a required paradigmatic generation procedure but the architecture remains general in the sense that given the appropriate substitutes for the morphological generator and POS tagger, one should obtain similar results.".
- 56 hasAuthorList authorList.
- 56 hasTopic Linguistics.
- 56 isPartOf proceedings.
- 56 keyword "Acquisition, Machine Learning".
- 56 keyword "Lexicon, lexical database".
- 56 keyword "Tagging".
- 56 title "Unsupervised Lexical Acquisition for Part of Speech Tagging".
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