metadata
license: mit
PoC (Patents with One Citation) dataset
This dataset is useful for training or evaluating models that predict patent-to-patent similarity, such as those used for patent searching.
It was developed and used for the training of an ML model that powers the PQAI search engine.
Details
The dataset contains 90,013 samples.
Each sample contains:
- a subject patent (
sp
) - its only citation (
cit
) - its CPC code (
cpc
) - a list of 10 patents (
sims
) that are similar tosp
(in that they share the CPC code) and published beforesp
Every line of the dataset is a JSON parsable string (.jsonl
format), which upon parsing given an array of this format:
[pn, cit, cpc, [...sims]]
Task
Given the subject patent sp
the task is to assign a similarity score to each patent [cit, ...sims]
. Ideally, the score should be maximum for cit
.
Metrics
It's a ranking task, so the following metrics make the most sense:
- DCG/NDCG
- Accuracy