Hierarchical Information Threading
Introduced by Narvala et al. in Effective Hierarchical Information Threading Using Network Community DetectionAn 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 Detection
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Language Modelling | 4 | 7.55% |
| Hint Generation | 3 | 5.66% |
| Speech Recognition | 2 | 3.77% |
| In-Context Learning | 2 | 3.77% |
| DeepFake Detection | 1 | 1.89% |
| EEG | 1 | 1.89% |
| Face Swapping | 1 | 1.89% |
| Large Language Model | 1 | 1.89% |
| Named Entity Recognition (NER) | 1 | 1.89% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
