Who Cited It

Question Answering For Toxicological Information Extraction

2022 · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · 1,569 citations · 5 from inside this corpus

No author records on this work.

Working with large amounts of text data has become hectic and time-consuming. In order to reduce human effort, costs, and make the process more efficient, companies and organizations resort to intelligent algorithms to automate and assist the manual work. This problem is also present in the field of toxicological analysis of chemical substances, where information needs to be searched from multiple documents. That said, we propose an approach that relies on Question Answering for acquiring information from unstructured data, in our case, English PDF documents containing information about physicochemical and toxicological properties of chemical substances. Experimental results confirm that our approach achieves promising results which can be applicable in the business scenario, especially if further revised by humans.

5 of 5 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
this paper works it cites works citing it node size = global citations · hover for the full title

What cites it, inside the corpus

Topics

Topic ModelingComputer Science
Natural Language Processing TechniquesComputer Science
Machine Learning and Data ClassificationComputer Science

Is this record sound?

suspect

Several fields of this record are missing or contradict each other. Treat its figures with suspicion — it is shown unaltered because correcting a source's record silently is worse than showing you the problem.

  • weakensThe source lists no authors for this work at all, so there is nobody to attribute it to and it appears on no author page.
  • weakensNo references are recorded despite 1,569 citations. A paper this heavily cited did not cite nothing, so the record is incomplete.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:57+00:00.

sha256 b3024609427ad450…