The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Measuring the semantic similarity of texts
Open accessAbstract
This paper presents a knowledge-based method for measuring the semantic-similarity of texts. While there is a large body of previous work focused on finding the semantic similarity of concepts and words, the application of these word-oriented methods to text similarity has not been yet explored. In this paper, we introduce a method that combines word-to-word similarity metrics into a text-to-text metric, and we show that this method outperforms the traditional text similarity metrics based on lexical matching.
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
Cites
BLEU: a method for automatic evaluation of machine translation
Papineni, K., Roukos, S., Ward, T., & Zhu, W.-J. (2001) · Proceedings of the 40th Annual Meeting on Association for Computational Linguistics - ACL '02 · doi:10.3115/1073083.1073135 · Cited by 21,344
An introduction to latent semantic analysis
Landauer, T. K., Foltz, P. W., & Laham, D. (1998) · Discourse Processes · doi:10.1080/01638539809545028 · Cited by 4,880
Cited by
BERTScore: Evaluating Text Generation with BERT
Zhang, T., Kishore, V., Wu, F., Weinberger, K. Q., & Artzi, Y. (2019) · arXiv · doi:10.48550/arxiv.1904.09675 · Cited by 2,865
MedSTS: a resource for clinical semantic textual similarity
Wang, Y., Afzal, N., Fu, S., Wang, L., Shen, F., Rastegar-Mojarad, M., & Liu, H. (2020) · Language Resources and Evaluation · doi:10.1007/s10579-018-9431-1 · Cited by 124
Uncertainty Estimation and Reduction of Pre-trained Models for Text Regression
Wang, Y., Beck, D., Baldwin, T., & Verspoor, K. (2022) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00483 · Cited by 23
Automating medical simulations
Gershov, S., Braunold, D., Spektor, R., Ioscovich, A., Raz, A., & Laufer, S. (2023) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2023.104446 · Cited by 8
Metadata
- Authors
- Corley, C., & Mihalcea, R.
- Venue
- Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment - EMSEE '05
- Published
- 2005
- Pages
- 13-18
- OpenAlex
- W1990524510
- Cited by
- 352
- References
- 2
- FWCI
- 11.92
- Type
- conference paper
- Language
- en
- Open access
- gold
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: Measuring the semantic similarity of texts. https://app.cochat.ai/papers/10.3115/1631862.1631865
- The paper
- Corley, C., & Mihalcea, R. (2005). Measuring the semantic similarity of texts. Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment - EMSEE '05. https://doi.org/10.3115/1631862.1631865
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.
