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---
license: cc0-1.0
task_categories:
- question-answering
- feature-extraction
language:
- en
pretty_name: PaperSeek OpenAlex Embeddings
size_categories:
- 100M<n<1B
---
# 📚 PaperSeek: OpenAlex English Titles & Abstracts (April 2025 Snapshot)
This dataset is part of the **[PaperSeek](https://github.com/Mohammadsaknini/PaperSeek)** framework, a semantic search engine designed for literature discovery using research questions and prior knowledge. PaperSeek is developed as part of a Master's thesis to explore novel approaches in enhancing academic search relevance.
## 📦 Dataset Overview
- **Source**: [OpenAlex](https://openalex.org/)
- **Snapshot Date**: April 1st, 2025
- **Language**: English
- **Contents**:
- Title
- Abstract
- Embedding
The dataset includes **102 million** research works, with English-language titles and abstracts extracted from the OpenAlex snapshot published on April 1st, 2025.
## 🧠 Embeddings
- **Model**: [Stella V5 1.5B]([https://huggingface.co/) (bfloat16 precision)
- **Embedding Prompt**: Title: {title}\n[SEP] Abstract: {abstract}
- **Output**: Dense embeddings suitable for semantic search and large-scale information retrieval.
## 🧪 Use Cases
- Semantic search
- Embedding-based retrieval
- Academic literature analysis
- NLP benchmarking on large-scale scientific text
## 📝 Citation
If you use this dataset, please cite/star the [PaperSeek](https://github.com/Mohammadsaknini/PaperSeek) project and OpenAlex as data sources. A formal citation for the Master's thesis will be provided once available.
## 📁 Data Structure
Each entry contains:
- `id`: Unique work ID (OpenAlex identifier)
- `title`: English title of the research work
- `abstract`: English abstract of the research work
- `embedding`: Float32 ncoded vector
## ⚠️ License & Use
- OpenAlex data is released under the [CC0 1.0 Universal (Public Domain Dedication)](https://creativecommons.org/publicdomain/zero/1.0/).
- Embeddings generated as part of the PaperSeek framework are released for research purposes.
## 🙋♂️ Contact
For questions or collaborations, feel free to get in touch through Hugging Face or via the Github. |