Cargando…
Linguistic Structure Prediction
A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic underst...
Autor principal: | |
---|---|
Lenguaje: | eng |
Publicado: |
Morgan & Claypool Publishers
2011
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/1486566 |
_version_ | 1780926149781618688 |
---|---|
author | Smith, Noah A |
author_facet | Smith, Noah A |
author_sort | Smith, Noah A |
collection | CERN |
description | A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W |
id | cern-1486566 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2011 |
publisher | Morgan & Claypool Publishers |
record_format | invenio |
spelling | cern-14865662021-04-22T00:16:59Zhttp://cds.cern.ch/record/1486566engSmith, Noah ALinguistic Structure PredictionComputing and ComputersA major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. WMorgan & Claypool Publishersoai:cds.cern.ch:14865662011 |
spellingShingle | Computing and Computers Smith, Noah A Linguistic Structure Prediction |
title | Linguistic Structure Prediction |
title_full | Linguistic Structure Prediction |
title_fullStr | Linguistic Structure Prediction |
title_full_unstemmed | Linguistic Structure Prediction |
title_short | Linguistic Structure Prediction |
title_sort | linguistic structure prediction |
topic | Computing and Computers |
url | http://cds.cern.ch/record/1486566 |
work_keys_str_mv | AT smithnoaha linguisticstructureprediction |