Papers by Amitra Salam

1 papers
TAP-DLND 1.0 : A Corpus for Document Level Novelty Detection (L18-1)

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Challenge: Detecting novelty of an entire document is an AI frontier problem . present state-of-the-art text matching techniques are unable to process such redundancy.
Approach: They propose a document-level novelty detection resource that can be used to benchmark techniques . they crawl news documents across several domains and use it to find out whether they contain new information .
Outcome: The proposed dataset is compared with a standard system for document novelty detection . the proposed system can detect elements that have not appeared before, or new or original .

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