The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Survey of Text Similarity Approaches
Open accessAbstract
Measuring the similarity between words, sentences, paragraphs and documents is an important component in various tasks such as information retrieval, document clustering, word-sense disambiguation, automatic essay scoring, short answer grading, machine translation and text summarization.This survey discusses the existing works on text similarity through partitioning them into three approaches; String-based, Corpus-based and Knowledgebased similarities.Furthermore, samples of combination between these similarities are presented.
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
Needleman, S. B., & Wunsch, C. D. (1970) · Journal of Molecular Biology · doi:10.1016/0022-2836(70)90057-4 · Cited by 11,288
Sentence similarity based on semantic nets and corpus statistics
Li, Y., McLean, D., Bandar, Z. A., O'Shea, J. D., & Crockett, K. (2006) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2006.130 · Cited by 819
Cited by
A large language model for electronic health records
Yang, X., Chen, A., PourNejatian, N., Shin, H. C., Smith, K. E., Parisien, C., Compas, C., Martin, C., Costa, A. B., Flores, M. G., et al. (2022) · npj Digital Medicine · doi:10.1038/s41746-022-00742-2 · Cited by 847
An AI-Based System for Formative and Summative Assessment in Data Science Courses
Vittorini, P., Menini, S., & Tonelli, S. (2021) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00230-2 · Cited by 105
LearningQ: A Large-Scale Dataset for Educational Question Generation
Chen, G., Yang, J., Hauff, C., & Houben, G.-J. (2018) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v12i1.14987 · Cited by 83
Evaluating the Evaluation of Diversity in Natural Language Generation
Tevet, G., & Berant, J. (2021) · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume · doi:10.18653/v1/2021.eacl-main.25 · Cited by 52
Measuring text similarity based on structure and word embedding
Farouk, M. (2020) · Cognitive Systems Research · doi:10.1016/j.cogsys.2020.04.002 · Cited by 47
Metadata
- Authors
- H.Gomaa, W., & A. Fahmy, A.
- Venue
- International Journal of Computer Applications
- Publisher
- Foundation of Computer Science
- Published
- 2013-04-18
- Volume
- 68
- Issue
- 13
- Pages
- 13-18
- ISSN
- 0975-8887 (ISSN-L)
- OpenAlex
- W2171313960
- Cited by
- 823
- References
- 2
- FWCI
- 29.08
- 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: A Survey of Text Similarity Approaches. https://app.cochat.ai/papers/10.5120/11638-7118
- The paper
- H.Gomaa, W., & A. Fahmy, A. (2013). A Survey of Text Similarity Approaches. International Journal of Computer Applications. https://doi.org/10.5120/11638-7118
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.