Northwestern University

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Methods for Improving Natural Language Processing Techniques with Linguistic Regularities Extracted from Large Unlabeled Text Corpora

Description:

Natural Language Processing methods have become increasingly important for a variety of high- and low-level tasks including speech recognition, question answering, and automatic language translation. The state of the art performance of these methods is continuously advancing, but reliance on labeled training data sets often creates an artificial upper bound...

Keyword:

Word Embeddings, Natural Language Processing, Polysemy, and Neural Networks

Subject:

Artificial intelligence and Computer science

Creator:

Lucas, Michael Ryan

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/12/2020

Date Created:

2017-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_677765 and http://dissertations.umi.com/northwestern:14760