[PDF] Top 20 Morphological Paradigms: Computational Structure and Unsupervised Learning
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Morphological Paradigms: Computational Structure and Unsupervised Learning
... a morphological paradigm is the longest common sub- string across the word forms, then this approach of stem identification works well only for strictly con- catenative morphology but not for anything that de- ... See full document
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Unsupervised Induction of Ukrainian Morphological Paradigms for the New Lexicon: Extending Coverage for Named Entities and Neologisms using Inflection Tables and Unannotated Corpora
... developing morphological lexicons can be found in (Ahlberg et ...word paradigms and/or clean datasets, such as lists of ‘headwords’ (lem- mas) from which paradigms are ...to learning ... See full document
11
Unsupervised learning of rhetorical structure with un topic models
... Supervised computational systems can be trained to mark up the AZ structure of a text automatically (see Section 2); the output of such systems has been shown to aid summarisation and human browsing of the ... See full document
12
Extending the Use of Adaptor Grammars for Unsupervised Morphological Segmentation of Unseen Languages
... of paradigms or ...machine learning: it is not in the same format as the desired output ...machine learning, as Sirts and Goldwater (2013) ... See full document
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Linguistica 5: Unsupervised Learning of Linguistic Structure
... of unsupervised learning of linguistic struc- ture, Linguistica 5 represents an important step for- ward by attempting to (i) induce structure that goes beyond morphology, and (ii) use it to improve ... See full document
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Unsupervised Dialog Structure Learning
... dialog structure from a set of task-oriented dialogs is an important challenge in computational ...dialog structure can shed light on how to analyze human dialogs, and more impor- tantly contribute ... See full document
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A Review of Unsupervised Artificial Neural Networks with Applications
... on unsupervised learning techniques and exploitation of the similarities between data [15, 16, ...topographically computational maps that learn by self-organisation of its ...competitive ... See full document
5
Probabilistic Hierarchical Clustering of Morphological Paradigms
... for learning morphological paradigms that are struc- tured within a ...of paradigms groups mor- phologically similar words close to each other in a tree ...ing morphological ... See full document
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Probabilistic Hierarchical Clustering Of Morphological Paradigms
... Unsupervised morphological segmentation of a text involves learning rules for segmenting words into their ...fully unsupervised, using only raw text as input to the learning ...require ... See full document
11
Unsupervised Multilingual Learning for Morphological Segmentation
... and Arabic, Aramaic, and English translations. The Semitic language family, of which Hebrew, Arabic, and Aramaic are members, is known for a highly productive morphology (Bravmann, 1977). Our re- sults indicate that ... See full document
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Unsupervised Induction of Ukrainian Morphological Paradigms for the New Lexicon: Extending Coverage for Named Entities and Neologisms using Inflection Tables and Unannotated Corpora
... developing morphological lexicons can be found in (Ahlberg et ...word paradigms and/or clean datasets, such as lists of ‘headwords’ (lem- mas) from which paradigms are ...to learning ... See full document
11
Supervised Learning of Complete Morphological Paradigms
... using unsupervised methods (Goldsmith, 2001; Creutz and Lagus, 2007; Monson, 2008; Poon et ...Some unsupervised work has specifi- cally targeted these sorts of phenomena by, for ex- ample, learning ... See full document
11
Morfessor FlatCat: An HMM Based Method for Unsupervised and Semi Supervised Learning of Morphology
... semi-supervised learning cannot be accomplished simply by adding the counts from an annotated data set, as it is not clear when to use hierarchy instead of segmenting a word directly in the ... See full document
9
Phenotypic differentiation of gastrointestinal microbes is reflected in their encoded metabolic repertoires
... of unsupervised machine-learning and computational mod- eling techniques to study individual and global differ- ences of the metabolic models and the original ... See full document
13
Unsupervised Learning of Name Structure From Coreference Data
... the structure and probabilities learned by these models, particularly the coreferent model, could be used for tasks other than assigning structure to ...name structure could do a better ...in ... See full document
7
An Unsupervised Method for Uncovering Morphological Chains
... produce morphological analysis based only on ortho- graphic ...for unsupervised morphological anal- ysis that integrates orthographic and seman- tic views of ...of morphological chains, from ... See full document
12
Graph Transductions and Typological Gaps in Morphological Paradigms
... many morphological paradigms is accurately delimited if one assumes that there are universally shared base hierarchies that may only be manipulated in narrowly restricted ...a computational ... See full document
13
Comparing Learners for Boolean partitions: Implications for Morphological Paradigms
... for learning paradigms, including ap- proaches quite different in spirit from the ones considered ...of learning as matching probabilities of the observed data ... See full document
9
Unsupervised Discovery of Phonological Categories through Supervised Learning of Morphological Rules
... Unsupervised Discovery of Phonological Categories through Supervised Learning of Morphological Rules U n s u p e r v i s e d Discovery of Phonological Categories through Supervised Learning of Morphol[.] ... See full document
6
Combining Hand crafted Rules and Unsupervised Learning in Constraint based Morphological Disambiguation
... Table 6: Average parses, recall and precision for text 270 after applying learned rules... Thus we have used very tight and conservative rules in hand-crafting.[r] ... See full document
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