Parallel Algorithms for Unsupervised Tagging
نویسندگان
چکیده
منابع مشابه
Parallel Algorithms for Unsupervised Tagging
We propose a new method for unsupervised tagging that finds minimal models which are then further improved by Expectation Maximization training. In contrast to previous approaches that rely on manually specified and multi-step heuristics for model minimization, our approach is a simple greedy approximation algorithm DMLC (DISTRIBUTEDMINIMUM-LABEL-COVER) that solves this objective in a single st...
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ژورنال
عنوان ژورنال: Transactions of the Association for Computational Linguistics
سال: 2014
ISSN: 2307-387X
DOI: 10.1162/tacl_a_00169