The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Data mining: an overview from a database perspective
Abstract
Mining information and knowledge from large databases has been recognized by many researchers as a key research topic in database systems and machine learning, and by many industrial companies as an important area with an opportunity of major revenues. Researchers in many different fields have shown great interest in data mining. Several emerging applications in information-providing services, such as data warehousing and online services over the Internet, also call for various data mining techniques to better understand user behavior, to improve the service provided and to increase business opportunities. In response to such a demand, this article provides a survey, from a database researcher's point of view, on the data mining techniques developed recently. A classification of the available data mining techniques is provided and a comparative study of such techniques is presented.
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Cites
Quinlan, J. R. (1986) · Machine Learning · doi:10.1007/bf00116251 · Cited by 21,439
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
Characterizing browsing strategies in the World-Wide web
Catledge, L. D., & Pitkow, J. E. (1995) · Computer Networks and ISDN Systems · doi:10.1016/0169-7552(95)00043-7 · Cited by 937
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Data mining: concepts and techniques
(2012) · Choice Reviews Online · doi:10.5860/choice.49-3305 · Cited by 28,531
Data Mining: Practical Machine Learning Tools and Techniques
(2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,437
Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008) · Decision Support Systems · doi:10.1016/j.dss.2007.07.001 · Cited by 3,613
Web usage mining: discovery and applications of usage patterns from Web data
Srivastava, J., Cooley, R., Deshpande, M., & Tan, P.-N. (2000) · ACM SIGKDD Explorations Newsletter · doi:10.1145/846183.846188 · Cited by 2,105
Discovering Frequent Closed Itemsets for Association Rules
Pasquier, N., Bastide, Y., Taouil, R., & Lakhal, L. (1999) · Lecture Notes in Computer Science · doi:10.1007/3-540-49257-7_25 · Cited by 1,378
Metadata
- Authors
- Chen, M.-S., Han, J., & Yu, P. S.
- Venue
- IEEE Transactions on Knowledge and Data Engineering
- Published
- 1996
- Volume
- 8
- Issue
- 6
- Pages
- 866-883
- ISSN
- 1041-4347 (ISSN-L)
- OpenAlex
- W2153028052
- Cited by
- 2,232
- References
- 3
- FWCI
- 89.34
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chen, M.-S., Han, J., & Yu, P. S. (1996). Data mining: an overview from a database perspective. IEEE Transactions on Knowledge and Data Engineering. https://doi.org/10.1109/69.553155
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.
