---
pretty_name: TopVenues Complete Corpus
license: other
language:
- en
task_categories:
- text-retrieval
tags:
- cybersecurity
- security
- bibliography
- literature-review
- dblp
size_categories:
- 100K<n<1M
configs:
- config_name: default
  data_files:
  - split: train
    path: train-*.parquet
---

# TopVenues Complete Corpus

The widest corpus the TopVenues pipeline produces: **118,817 distinct
publications** across **40 venues** (2017-2026), every record carrying a
canonical BibTeX entry and a DBLP key.

Built by a monotonic union of the `full-40` and `security-20` profiles. Neither
was a superset of the other, so the union recovers records and abstracts that
either profile alone was missing.

- **Code / tool:** <https://github.com/sidneibarbieri/topvenues-tool>
- **Profile:** `complete-40`
- **Snapshot SHA-256 (gzip):** `6f837953c3cc2d92da74879ad61ef575808f875a2f27d87bab113c698e864dfc`

## Not a paper denominator

This corpus is a tool release, not the denominator of any paper. Two separate
frozen snapshots back the published work and are **not** replaced by this one:

| Release | Records | Cited by |
|---|---|---|
| `submitted-11` | 9,925 | the full paper |
| `security-20` (dataset [`sidneibarbieri/topvenues`](https://huggingface.co/datasets/sidneibarbieri/topvenues)) | 20,305 | the tools-track paper |

Any measurement must name the snapshot that produced its denominator. Numbers
from one corpus do not transfer to another merely because the software is shared.

## One record per work

Records are deduplicated by DBLP key, field-wise: where the same key was
ingested more than once, each field keeps its most complete value, so the
surviving record is at least as complete as any copy that fed it. That recovered
2,743 BibTeX entries, 1,483 abstracts, 415 author lists and 13 titles truncated
at superscripts. Result: **118,817 rows, 118,817 distinct
keys**, so a count of rows is a count of distinct publications.

## Abstract coverage is uneven, by construction

14,289 of 118,817 records carry an abstract (12.0%). That
figure is low because the corpus deliberately includes large AI and systems
venues whose records were ingested for bibliographic completeness without
abstract enrichment. Coverage on the security venues is high. 21 of
40 venues carry abstracts at all:

| Venue | Records | Abstracts | Coverage |
|---|---:|---:|---:|
| USENIX Security | 2,103 | 2,056 | 97.8% |
| ACM CCS | 1,972 | 1,971 | 99.9% |
| TrustCom | 1,915 | 1,912 | 99.8% |
| ACM Computing Surveys | 1,813 | 1,812 | 99.9% |
| IEEE S&P | 1,166 | 1,165 | 99.9% |
| NDSS | 1,059 | 1,058 | 99.9% |
| ACM ASIA CCS | 837 | 827 | 98.8% |
| IEEE Communications Surveys & Tutorials | 833 | 804 | 96.5% |
| ACSAC | 509 | 509 | 100.0% |
| IEEE CNS | 381 | 381 | 100.0% |
| IEEE EURO S&P | 339 | 339 | 100.0% |
| ACM CODASPY | 316 | 281 | 88.9% |
| ACM WiSec | 314 | 270 | 86.0% |
| HotNets | 245 | 245 | 100.0% |
| RAID | 290 | 222 | 76.6% |
| ACM SACMAT | 176 | 176 | 100.0% |
| IEEE SaTML | 127 | 127 | 100.0% |
| ACM AISec | 77 | 73 | 94.8% |
| ESORICS | 598 | 39 | 6.5% |
| Foundations and Trends in Privacy and Security | 20 | 20 | 100.0% |
| USENIX WOOT | 18 | 2 | 11.1% |
| AAAI | 20,085 | 0 | 0.0% |
| NeurIPS | 16,527 | 0 | 0.0% |
| EMNLP | 12,817 | 0 | 0.0% |
| ICML | 11,971 | 0 | 0.0% |
| ACL | 11,294 | 0 | 0.0% |
| ICLR | 10,680 | 0 | 0.0% |
| IJCAI | 6,501 | 0 | 0.0% |
| ACM KDD | 4,110 | 0 | 0.0% |
| NAACL | 4,107 | 0 | 0.0% |
| ACM MobiCom | 993 | 0 | 0.0% |
| ACM SenSys | 808 | 0 | 0.0% |
| ACM MobiSys | 655 | 0 | 0.0% |
| USENIX NSDI | 542 | 0 | 0.0% |
| ACM EuroSys | 518 | 0 | 0.0% |
| USENIX ATC | 518 | 0 | 0.0% |
| ACM IMC | 466 | 0 | 0.0% |
| ACM SIGCOMM | 452 | 0 | 0.0% |
| ACM SIGMETRICS | 376 | 0 | 0.0% |
| ACM HotMobile | 289 | 0 | 0.0% |

## Usage

```python
from datasets import load_dataset

corpus = load_dataset("sidneibarbieri/topvenues-complete", split="train")
security = corpus.filter(lambda r: r["abstract"] and "USENIX" in (r["event"] or ""))
```

## Fields

`paper_id`, `key` (DBLP), `title`, `authors`, `event`, `venue`, `area`, `year`,
`paper_type`, `pages`, `url`, `ee` (DOI), `abstract`, `bibtex`.

## License

Metadata originates from DBLP (CC0) and open scholarly APIs. Abstracts remain
under their publishers' terms and are included for research use.