Predicting Linguistic Structure with Incomplete and Cross-Lingual Supervision

Predicting Linguistic Structure with Incomplete and Cross-Lingual Supervision

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Contemporary approaches to natural language processing are predominantly based on statistical machine learning from large amounts of text, which has been manually annotated with the linguistic structure of interest. However, such complete supervision is currently only available for the world's...

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Bibliographic Details
Main Author: Täckström, Oscar
Format: Doctoral Thesis
Language:English
Published: Uppsala universitet, Institutionen för lingvistik och filologi 2013
Subjects:
linguistic structure prediction
structured prediction
latent-variable model
semi-supervised learning
multilingual learning
cross-lingual learning
indirect supervision
partial supervision
ambiguous supervision
part-of-speech tagging
dependency parsing
named-entity recognition
sentiment analysis
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-197610
http://nbn-resolving.de/urn:isbn:978-91-554-8631-0

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-197610
http://nbn-resolving.de/urn:isbn:978-91-554-8631-0

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