Update README.md

README.md

@@ -1,3 +1,58 @@
 ---
 license: cc-by-nc-4.0
+pretty_name: MerRec
+size_categories:
+- 1B<n<10B
+language:
+- en
+tags:
+- recommendation
+- sequential recommendation
+- click-through rate prediction
+- e-commerce
 ---
+
+# MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation Systems
+
+This repository contains the dataset accompanying the paper [MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation Systems](https://arxiv.org/abs/2402.14230).
+
+Contributors: Lichi Li, Zainul Abi Din, Zhen Tan, Sam London, Tianlong Chen, Ajay Daptardar
+
+## Overview
+
+The MerRec dataset is a large-scale, highly diverse, thoroughly anonymized and derived subset of item interaction event sequence data from Mercari, the C2C marketplace e-commerce platform. It is designed for researchers to study recommendation related tasks on a rich C2C environment with many item features.
+
+Some basic statistics are:
+
+- Unique users: Over 5 million
+- Unique items: Over 80 million
+- Unique events: Over 1 billion
+- Unique sessions: Over 200 million
+- Item title text tokens: Over 8 billion
+
+For a detailed walkthrough and an extensive list of accurate statistics, feature interpretations, preprocessing procedure, please refer to the paper.
+
+## File Organization
+
+The MerRec dataset is divided into 6 directories, each containing about 500 Parquet shards from a particular month in 2023.
+
+## Experiments
+
+Code implementation used for the experiment section of the paper can be found [here](https://github.com/mercari/mercari-ml-merrec-pub-us).
+
+## BibTeX
+
+```bibtex
+@misc{li2024merrec,
+      title={MerRec: A Large-scale Multipurpose Mercari Dataset for Consumer-to-Consumer Recommendation Systems}, 
+      author={Lichi Li and Zainul Abi Din and Zhen Tan and Sam London and Tianlong Chen and Ajay Daptardar},
+      year={2024},
+      eprint={2402.14230},
+      archivePrefix={arXiv},
+      primaryClass={cs.IR}
+}
+```
+
+## License
+
+Dataset license: [CC BY-NC 4.0 International](https://creativecommons.org/licenses/by-nc/4.0/legalcode.en)