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Demir et al., 2014 - Google Patents

Improving named entity recognition for morphologically rich languages using word embeddings

Demir et al., 2014

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Document ID
7911469945576866091
Author
Demir H
Özgür A
Publication year
Publication venue
2014 13th international conference on machine learning and applications

External Links

Snippet

In this paper, we addressed the Named Entity Recognition (NER) problem for morphologically rich languages by employing a semi-supervised learning approach based on neural networks. We adopted a fast unsupervised method for learning continuous vector …
Continue reading at www.cmpe.boun.edu.tr (PDF) (other versions)

Classifications

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    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30634—Querying
    • G06F17/30657—Query processing
    • G06F17/30675—Query execution
    • G06F17/30684—Query execution using natural language analysis
    • G—PHYSICS
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    • G06F17/2765—Recognition
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