An unsupervised approach for identifying Hierarchical Information Threads by analysing the network of related articles in a collection. In particular, HINT leverages article timestamps and the 5W1H questions to identify related articles about an event or discussion. HINT then constructs a network representation of the articles, and identify threads as strongly connected hierarchical network communities.
Source: Effective Hierarchical Information Threading Using Network Community DetectionPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Language Modelling | 8 | 6.72% |
Language Modeling | 7 | 5.88% |
Hint Generation | 6 | 5.04% |
Large Language Model | 5 | 4.20% |
Sentence | 3 | 2.52% |
Retrieval | 3 | 2.52% |
Sentiment Analysis | 2 | 1.68% |
Arithmetic Reasoning | 2 | 1.68% |
Decoder | 2 | 1.68% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |