The DOI matches its Crossref record.
Mining Intelligence and Knowledge Exploration: Second International Conference, MIKE 2014, Cork, Ireland, December 10-12, 2014. Proceedings
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Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As such, autoencoders are most commonly used for feature extraction and dimensionality reduction [120,122,123,124,125,126,133,134,135,136,137,138,139,140,141].”
From Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances (2022) · cites this paper as [125]
In the citing paper
“The result reveals that the stacked autoencoder has the highest accuracy of 92.16% and provides a 7% advantage over traditional methods with hand-crafted features.”
From Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances (2022) · cites this paper as [125]
Citations
Cited by
Deep learning for sensor-based activity recognition: A survey
Wang, J., Chen, Y., Hao, S., Peng, X., & Hu, L. (2019) · Pattern Recognition Letters · doi:10.1016/j.patrec.2018.02.010 · Cited by 2,014
Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances
Zhang, S., Li, Y., Zhang, S., Shahabi, F., Xia, S., Deng, Y., & Alshurafa, N. (2022) · Sensors · doi:10.3390/s22041476 · Cited by 625
Soleimani, E., & Nazerfard, E. (2021) · Neurocomputing · doi:10.1016/j.neucom.2020.10.056 · Cited by 146
Identifying machine learning techniques for classification of target advertising
Choi, J.-A., & Lim, K. (2020) · ICT Express · doi:10.1016/j.icte.2020.04.012 · Cited by 139
Cruz, E. F., & Rosado da Cruz, A. M. (2023) · Cleaner and Responsible Consumption · doi:10.1016/j.clrc.2023.100138 · Cited by 42
Metadata
- Authors
- Prasath, R., O’Reilly, P., & Kathirvalavakumar, T.
- Affiliations
- University College Cork (IE)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2014
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W4251398444
- Cited by
- 39
- References
- 0
- Citations by year
- 2025: 2 · 2024: 3 · 2023: 5 · 2022: 7 · 2021: 3 · 2020: 9 · 2019: 3 · 2018: 2 · 2017: 1 · 2016: 4
- FWCI
- 1.42
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- DIAL (Catholic University of Leuven) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Data Mining
- Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
- Keywords
- knowledge exploration, data mining, knowledge discovery
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.
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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 Intelligence and Knowledge Exploration: Second International Conference, MIKE 2014, Cork, Ireland, December 10-12, 2014. Proceedings. https://app.cochat.ai/papers/10.1007/978-3-319-13817-6
- The paper
- Prasath, R., O’Reilly, P., & Kathirvalavakumar, T. (2014). Mining Intelligence and Knowledge Exploration: Second International Conference, MIKE 2014, Cork, Ireland, December 10-12, 2014. Proceedings. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-13817-6
