Data · dataset · 2022
StyleChangeDetection
Listed in Hugging Face Datasets
The goal of the style change detection task is to identify text positions within a given multi-author document at which the author switches.
Description
Detecting these positions is a crucial part of the authorship identification process, and for multi-author document analysis in general. Access to the dataset needs to be requested from zenodo.
Links
Where it is published
- Hugging Face dataset page huggingface.co/datasets/community-datasets/style_change_detection ↗
landing page · from Hugging Face
Catalogue records · 1
- Hub API huggingface.co/api/datasets/community-datasets/style_change_detection ↗
metadata API · from Hugging Face
Topics
- From keywords
- Computer Science & AI
- Inferred from text
- Text 75%
Provenance · 1 source records, 8 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Hugging Face Datasets | community-datasets/style_change_detection | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · Hugging Face | connector:huggingface@1.0.0 | /gated |
| concepts[field].local:field:computer-science-ai | mapping · Hugging Face | connector:huggingface@1.0.0 | |
| concepts[modality].local:modality:text | enrichment · Hugging Face | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| description | source · Hugging Face | connector:huggingface@1.0.0 | /description |
| publication_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| title | source · Hugging Face | connector:huggingface@1.0.0 | /id |
| updated_date | source · Hugging Face | connector:huggingface@1.0.0 |