Name
Title | ||
|---|---|---|
Is Your Document Novel? Let Attention Guide You. An Attention-Based Model For Document-Level Novelty Detection |
Abstract | ||
|---|---|---|
Detecting, whether a document contains sufficient new information to be deemed as novel, is of immense significance in this age of data duplication. Existing techniques for document-level novelty detection mostly perform at the lexical level and are unable to address the semantic-level redundancy. These techniques usually rely on handcrafted features extracted from the documents in a rule-based or traditional feature-based machine learning setup. Here, we present an effective approach based on neural attention mechanism to detect document-level novelty without any manual feature engineering. We contend that the simple alignment of texts between the source and target document(s) could identify the state of novelty of a target document. Our deep neural architecture elicits inference knowledge from a large-scale natural language inference dataset, which proves crucial to the novelty detection task. Our approach is effective and outperforms the standard baselines and recent work on document-level novelty detection by a margin of similar to 3% in terms of accuracy. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1017/S1351324920000194 | NATURAL LANGUAGE ENGINEERING |
Keywords | DocType | Volume |
Document-Level Novelty Detection, Decomposable Attention, Natural Language Inference, Document Classification | Journal | 27 |
Issue | ISSN | Citations |
4 | 1351-3249 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tirthankar Ghosal | 1 | 8 | 8.40 |
| Vignesh Edithal | 2 | 0 | 0.34 |
| Asif Ekbal | 3 | 737 | 119.31 |
| Pushpak Bhattacharyya | 4 | 795 | 186.21 |
| Srinivasa Satya Sameer Kumar Chivukula | 5 | 0 | 0.34 |
| George Tsatsaronis | 6 | 0 | 0.34 |