DBLP Scraper

Scrape computer-science publications from the DBLP bibliography by keyword — title, authors, venue, year, publication type, DOI, and links. DBLP indexes papers from IEEE, ACM, Springer, USENIX, NeurIPS and other CS conferences and journals. Built on DBLP's public search API: no API key or setup needed.

Search a topic like graph neural network, get a clean, dated list of matching papers — ready to export to CSV, Excel, or JSON, or to power a research monitor.

Features

• Authoritative CS source — reads the public DBLP publication search API.
• Clean author lists — normalizes single-author, multi-author, and author-less records into a simple array of names.
• Rich links — each row links to the canonical publisher URL (or DOI, or DBLP record).
• Client-side filters — keep only recent work (yearFrom) or specific venues (venueFilter, e.g. IEEE, ACM, NeurIPS).
• Monitoring-ready — schedule it on your keywords and catch new papers as they get indexed.

Use cases

• Literature review & discovery — researchers and students building reading lists on a topic.
• Citation & venue analysis — group publications by venue, year, or type.
• Research monitoring — schedule daily/weekly to catch new papers on your keywords.
• Dataset building — assemble structured bibliographies for downstream analysis.

Input

Field	Type	Description
searchQueries	string[]	Search queries, e.g. graph neural network, consensus protocol.
maxItems	integer	Max publications per query. Default 100.
yearFrom	integer	Keep only publications from this year onward.
venueFilter	string[]	Keep only venues containing any of these strings (e.g. IEEE, ACM, NeurIPS).

Example

{
  "searchQueries": ["deep learning", "antenna"],
  "yearFrom": 2020,
  "venueFilter": ["IEEE", "ACM"],
  "maxItems": 100
}

Output

{
  "title": "An enhanced deep learning framework for DeepFake detection.",
  "authors": ["B. G. Deepa", "C. K. Lokesh", "D. Umamaheswari"],
  "venue": "Discov. Comput.",
  "year": "2026",
  "type": "Journal Articles",
  "doi": "10.1007/S10791-025-09890-X",
  "url": "https://doi.org/10.1007/s10791-025-09890-x",
  "dblpKey": "journals/ir/DeepaLUAYS26",
  "pages": "18",
  "volume": "29",
  "number": "1",
  "query": "deep learning",
  "scrapedAt": "2026-08-12T00:00:00.000Z"
}

Download the dataset as JSON, CSV, Excel, or XML, or pull it via the Apify API.

Pricing

Pay-per-event: $0.01 per run start (per GB of run memory) plus $0.50 per 1,000 publications. You only pay for publications actually returned. See the Pricing tab for current rates.

FAQ

Do I need an API key? No. DBLP's search API is public and free; this Actor packages it into clean, filtered rows.

How does the venue filter work? It's a case-insensitive substring match — IEEE keeps every venue whose name contains "IEEE" (e.g. IEEE Access, IEEE Commun. Lett.).

Can I monitor for new papers? Yes — schedule the Actor (e.g. weekly) with your keywords.

Disclaimer

This Actor uses the public DBLP search API. It is not affiliated with or endorsed by DBLP or Schloss Dagstuhl. The data is public; you are responsible for how you use it.