Predicting Linguistic Structure with Incomplete and Cross-Lingual Supervision

Predicting Linguistic Structure with Incomplete and Cross-Lingual Supervision

Show other versions (1)

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...

Full description

Bibliographic Details
Main Author: Täckström, Oscar
Format: Doctoral Thesis
Language:English
Published: SICS 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:ri:diva-24193
http://nbn-resolving.de/urn:isbn:978-91-554-8631-0

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-24193
http://nbn-resolving.de/urn:isbn:978-91-554-8631-0

Similar Items