The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Exploratory mining and pruning optimizations of constrained associations rules
Abstract
From the standpoint of supporting human-centered discovery of knowledge, the present-day model of mining association rules suffers from the following serious shortcomings: (i) lack of user exploration and control, (ii) lack of focus, and (iii) rigid notion of relationships. In effect, this model functions as a black-box, admitting little user interaction in between. We propose, in this paper, an architecture that opens up the black-box, and supports constraint-based, human-centered exploratory mining of associations. The foundation of this architecture is a rich set of constraint constructs, including domain, class, and SQL-style aggregate constraints, which enable users to clearly specify what associations are to be mined. We propose constrained association queries as a means of specifying the constraints to be satisfied by the antecedent and consequent of a mined association.
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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
Cited by
Data mining: concepts and techniques
(2012) · Choice Reviews Online · doi:10.5860/choice.49-3305 · Cited by 28,531
Mining frequent patterns without candidate generation
Han, J., Pei, J., & Yin, Y. (2000) · ACM SIGMOD Record · doi:10.1145/335191.335372 · Cited by 6,402
Self-citationFrequent 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
Self-citationEfficient mining of partial periodic patterns in time series database
Han, J., Dong, G., & Yin, Y. (1999) · Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337) · doi:10.1109/icde.1999.754913 · Cited by 587
Self-citation(2003) · Cited by 165
Metadata
- Authors
- Ng, R. T., Lakshmanan, L. V. S., Han, J., & Pang, A.
- Venue
- Proceedings of the 1998 ACM SIGMOD international conference on Management of data
- Publisher
- ACM
- Published
- 1998-06
- Pages
- 13-24
- ISSN
- 0730-8078 (ISSN-L)
- OpenAlex
- W2085638007
- Cited by
- 715
- References
- 1
- FWCI
- 33.28
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Ng, R. T., Lakshmanan, L. V. S., Han, J., & Pang, A. (1998). Exploratory mining and pruning optimizations of constrained associations rules. Proceedings of the 1998 ACM SIGMOD international conference on Management of data. https://doi.org/10.1145/276304.276307
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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