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Pfahler et al., 2017 - Google Patents

Learning low-rank document embeddings with weighted nuclear norm regularization

Pfahler et al., 2017

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Document ID
16443428663580491248
Author
Pfahler L
Morik K
Elwert F
Tabti S
Krech V
Publication year
Publication venue
2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA)

External Links

Snippet

Recently, neural embeddings of documents have shown success in various language processing tasks. These low-dimensional and dense feature vectors of text documents capture semantic similarities better than traditional methods. However, the underlying …
Continue reading at www-ai.cs.tu-dortmund.de (PDF) (other versions)

Classifications

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    • G06F17/3061—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F17/30705—Clustering or classification
    • G06F17/3071—Clustering or classification including class or cluster creation or modification
    • G—PHYSICS
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