Update README.md

README.md

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----
-license: cc-by-nc-sa-4.0
----
+---
+license: cc-by-nc-sa-4.0
+pretty_name: "DAPFAM –\_Domain‑Aware Patent Retrieval at the Family level"
+tags:
+- patents
+- retrieval
+- information‑retrieval
+- cross‑domain
+- patent
+- fulltext
+size_categories:
+- 10K<n<100K
+language:
+- en
+---
+
+# Dataset Card for **DAPFAM**
+
+See the accompanying paper: **Ayaou et al., 2025 — “DAPFAM: A Domain‑Aware Patent Retrieval Dataset Aggregated at the Family Level” (arXiv:2506.22141).**
+
+## Summary
+
+DAPFAM provides **1 247 balanced query patent families** and **45 336 target families** with forward/backward‑citation relevance labels (≈ 50 K pairs). Each relevant link is explicitly marked **in‑domain** or **out‑of‑domain** according to IPC 3‑char overlap, enabling rigorous cross‑domain evaluation.
+
+* Full text **(title · abstract · claims · description)** plus rich metadata for *every* family.
+* Multi‑jurisdictional, English‑only text (families may originate in US, JP, EP, CN, …).
+* Parquet qrel file: `qrels_all.parquet`.
+
+## Dataset Structure
+
+```
+corpus.parquet   # 45 336 rows, targets – every original column from the paper
+queries.parquet  # 1 247 rows,   queries – same columns + abstract_keywords
+qrels_all.parquet  # (all | in | out) four‑column tables → query_id · relevant_id · relevance_score · domain_rel
+```
+
+> **No columns are renamed or discarded.**  Down‑stream loaders can combine fields as needed (e.g. `title_en + "
+" + abstract_en + ...`).
+
+
+## How to load
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("datalyes/dapfam", data_files="queries.parquet", split="train")
+print(ds[0].keys())
+```
+
+## Citation
+
+```
+@misc{ayaou2025dapfam,
+    title={DAPFAM: A Domain-Aware Patent Retrieval Dataset Aggregated at the Family Level},
+    author={Iliass Ayaou and Denis Cavallucci and Hicham Chibane},
+    year={2025},
+    eprint={2506.22141},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
+## Quick Stats
+
+* **Queries**: 1,247
+* **Corpus (targets)**: 45,336
+* **Qrels (all)**: 49,869
+* **Qrels (in)**: 19,736
+* **Qrels (out)**: 5,193