Reinhard rapp

This paper quantitatively investigates in how far local context is useful to disambiguate the senses of an ambiguous word. This is done by comparing the co-occurrence frequencies of particular context words. First, one context word representing a certain sense is chosen, and then the co-occurrence frequencies with two other context words, one of the same and one of another sense, are compared. As expected, it turns out that context words belonging to the same sense have considerably higher co-occurrence frequencies than words belonging to different senses. ...

4p bunthai_1 06-05-2013 33 1   Download

C o m m o n algorithms for sentence and word-alignment allow the automatic identification of word translations from paxalhl texts. This study suggests that the identification of word translations should also be possible with non-paxMlel and even unrelated texts. The m e t h o d proposed is based on the assumption t h a t there is a correlation between the patterns of word cooccurrences in texts of different languages.

3p bunmoc_1 20-04-2013 40 2   Download

Recent studies in word sense induction are based on clustering global co-occurrence vectors, i.e. vectors that reflect the overall behavior of a word in a corpus. If a word is semantically ambiguous, this means that these vectors are mixtures of all its senses. Inducing a word’s senses therefore involves the difficult problem of recovering the sense vectors from the mixtures.

4p bunbo_1 17-04-2013 32 2   Download