Papers by Srinivasa Satya Sameer Kumar Chivukula

1 papers
Novelty Goes Deep. A Deep Neural Solution To Document Level Novelty Detection (C18-1)

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Challenge: Existing methods for document-level novelty detection are limited and do not require manual feature engineering.
Approach: They propose a deep Convolutional Neural Networks based model to classify a document as novel or redundant on the basis of documents already seen by the system.
Outcome: The proposed model outperforms the state-of-the-art on a document-level novelty detection dataset by a margin of 5% in terms of accuracy.

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