README.md

metadata

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
configs:
  - config_name: corpus
    data_files: corpus.parquet
  - config_name: queries
    data_files: queries.parquet
  - config_name: relations
    data_files: qrels_all.parquet

DAPFAM dataset

For more details on the dataset construction and baseline experimentations, see the accompanying paper: Ayaou et al., 2025 — “DAPFAM: A Domain‑Aware Patent Retrieval Dataset Aggregated at the Family Level”(Here) .

Summary

DAPFAM provides 1 247 domain balanced full-text query patent families and 45 336 full-text 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

How to load

from datasets import load_dataset

#According to your usage, you might not need to load all 3 subsets

dc = load_dataset("datalyes/DAPFAM_patent", "corpus")

dq = load_dataset("datalyes/DAPFAM_patent", "queries")

dr = load_dataset("datalyes/DAPFAM_patent", "relations")

Citation

If you find our paper or dataset helpful, please consider citing as follows:

@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