The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Data mining and knowledge discovery: making sense out of data
Abstract
Current computing and storage technology is rapidly outstripping society's ability to make meaningful use of the torrent of available data. Without a concerted effort to develop knowledge discovery techniques, organizations stand to forfeit much of the value from the data they currently collect and store.
Overview
The claims and statistics of this paper haven’t been checked yet.
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Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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Self-check
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Citations
Cites
An Introduction to Computational Learning Theory
Kearns, M. J., & Vazirani, U. (1994) · doi:10.7551/mitpress/3897.001.0001 · Cited by 1,697
Cited by
Geurts, P., Ernst, D., & Wehenkel, L. (2006) · Machine Learning · doi:10.1007/s10994-006-6226-1 · Cited by 9,300
(1999) · doi:10.1162/089976600300015565 · Cited by 2,799
Text classification from labeled and unlabeled documents using EM
Nigam, K., Mccallum, A. K., Thrun, S., & Mitchell, T. (2000) · Machine Learning · doi:10.1023/a:1007692713085 · Cited by 2,736
(2000) · Cited by 1,467
Facial expression recognition from video sequences: temporal and static modeling
Cohen, I., Sebe, N., Garg, A., Chen, L. S., & Huang, T. S. (2003) · Computer Vision and Image Understanding · doi:10.1016/s1077-3142(03)00081-x · Cited by 874
Metadata
- Authors
- Feyyad, U. M.
- Venue
- IEEE Expert
- Published
- 1996-10
- Volume
- 11
- Issue
- 5
- Pages
- 20-25
- ISSN
- 0885-9000 (ISSN-L)
- OpenAlex
- W2138745909
- Cited by
- 4,612
- References
- 1
- FWCI
- 111.68
- 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 ›
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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.
