The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Mining generalized association rules
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
Mining association rules between sets of items in large databases
Agrawal, R., Imieliński, T., & Swami, A. (1993) · Proceedings of the 1993 ACM SIGMOD international conference on Management of data · doi:10.1145/170035.170072 · Cited by 14,907
Self-citationFast algorithms for mining association rules
Agrawal, R., & Srikant, R. (1998) · Cited by 11,307
Self-citationFast Algorithms for Mining Association Rules in Large Databases
Agrawal, R., & Srikant, R. (1994) · Very Large Data Bases · Cited by 9,419
Self-citationSpencer, J. (1991) · Medical Entomology and Zoology · Cited by 4,310
Advances in knowledge discovery and data mining
(1996) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(96)90007-3 · Cited by 2,971
Fast discovery of association rules
Agrawal, R., Mannila, H., Srikant, R., Toivonen, H. T. T., & Verkamo, A. I. (1996) · Knowledge Discovery and Data Mining · Cited by 2,376
Self-citationKnowledge Discovery in Databases
Piateski, G., & Frawley, W. (1991) · The MIT Press eBooks · Cited by 1,749
An Efficient Algorithm for Mining Association Rules in Large Databases
Savasere, A., Omiecinski, E. R., & Navathe, S. B. (1995) · Cited by 1,590
An effective hash-based algorithm for mining association rules
Park, J. S., Chen, M.-S., & Yu, P. S. (1995) · Proceedings of the 1995 ACM SIGMOD international conference on Management of data - SIGMOD '95 · doi:10.1145/223784.223813 · Cited by 1,406
Sampling Large Databases for Association Rules
Toivonen, H. T. T. (1996) · Cited by 1,089
Cited by
Data mining: concepts and techniques
(2012) · Choice Reviews Online · doi:10.5860/choice.49-3305 · Cited by 28,531
Top 10 algorithms in data mining
Wu, X., Kumar, V., Ross Quinlan, J., Ghosh, J., Yang, Q., Motoda, H., McLachlan, G. J., Ng, A., Liu, B., Yu, P. S., et al. (2008) · Knowledge and Information Systems · doi:10.1007/s10115-007-0114-2 · Cited by 5,667
Mining sequential patterns: Generalizations and performance improvements
Srikant, R., & Agrawal, R. (1996) · Lecture Notes in Computer Science · doi:10.1007/bfb0014140 · Cited by 2,711
Self-citation(2000) · Cited by 1,467
Frequent pattern mining: current status and future directions
Han, J., Cheng, H., Xin, D., & Yan, X. (2007) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-006-0059-1 · Cited by 1,380
Metadata
- Authors
- Srikant, R., & Agrawal, R.
- Venue
- Future Generation Computer Systems
- Publisher
- Elsevier BV
- Published
- 1997-11
- Volume
- 13
- Issue
- 2-3
- Pages
- 161-180
- ISSN
- 0167-739X (ISSN-L)
- OpenAlex
- W1520890006
- Cited by
- 1,618
- References
- 18
- FWCI
- 192.42
- Type
- journal article
- Language
- en
- Open access
- closed
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: Mining generalized association rules. https://app.cochat.ai/papers/10.1016/s0167-739x(97)00019-8
- The paper
- Srikant, R., & Agrawal, R. (1997). Mining generalized association rules. Future Generation Computer Systems. https://doi.org/10.1016/s0167-739x(97)00019-8
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.
