The DOI matches its Crossref record.
SCISOR: extracting information from on-line news
Open accessAbstract
The future of natural language text processing is examined in the SCISOR prototype. Drawing on artificial intelligence techniques, and applying them to financial news items, this powerful tool illustrates some of the future benefits of natural language analysis through a combination of bottom-up and top-down processing.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Cowie, J., & Lehnert, W. (1996) · Communications of the ACM · doi:10.1145/234173.234209 · Cited by 731
Extracting company names from text
Rau, L. F. (2002) · [1991] Proceedings. The Seventh IEEE Conference on Artificial Intelligence Application · doi:10.1109/caia.1991.120841 · Cited by 264
Self-citationAdvantages of query biased summaries in information retrieval
Tombros, A., & Sanderson, M. (1998) · Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/290941.290947 · Cited by 241
Fast generation of abstracts from general domain text corpora by extracting relevant sentences
Zechner, K. (1996) · Proceedings of the 16th conference on Computational linguistics - · doi:10.3115/993268.993338 · Cited by 107
Metadata
- Authors
- Jacobs, P. S., & Rau, L. F.
- Venue
- Communications of the ACM
- Published
- 1990-11
- Volume
- 33
- Issue
- 11
- Pages
- 88-97
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2079690930
- Cited by
- 215
- References
- 0
- FWCI
- 12.66
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: SCISOR: extracting information from on-line news. https://app.cochat.ai/papers/10.1145/92755.92769
- The paper
- Jacobs, P. S., & Rau, L. F. (1990). SCISOR: extracting information from on-line news. Communications of the ACM. https://doi.org/10.1145/92755.92769
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
