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---
annotations_creators:
- unknown
language_creators:
- unknown
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- unknown
task_categories:
- other
task_ids:
- natural-language-inference
- semantic-similarity-scoring
- text-scoring
pretty_name: CORE Deduplication of Scholarly Documents
tags:
- deduplication
---
# Dataset Card for CORE Deduplication
## Dataset Description
- **Homepage:** [https://core.ac.uk/about/research-outputs](https://core.ac.uk/about/research-outputs)
- **Repository:** [https://core.ac.uk/datasets/core_2020-05-10_deduplication.zip](https://core.ac.uk/datasets/core_2020-05-10_deduplication.zip)
- **Paper:** [Deduplication of Scholarly Documents using Locality Sensitive Hashing and Word Embeddings](http://oro.open.ac.uk/id/eprint/70519)
- **Point of Contact:** [CORE Team](https://core.ac.uk/about#contact)
- **Size of downloaded dataset files:** 204 MB
### Dataset Summary
CORE 2020 Deduplication dataset (https://core.ac.uk/documentation/dataset) contains 100K scholarly documents labeled as duplicates/non-duplicates.
### Languages
The dataset language is English (BCP-47 `en`)
### Citation Information
```
@inproceedings{dedup2020,
title={Deduplication of Scholarly Documents using Locality Sensitive Hashing and Word Embeddings},
author={Gyawali, Bikash and Anastasiou, Lucas and Knoth, Petr},
booktitle = {Proceedings of 12th Language Resources and Evaluation Conference},
month = may,
year = 2020,
publisher = {France European Language Resources Association},
pages = {894-903}
}
```
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