DataMIME (Data: Mine It More Efficiently)
Summary: DataMIME is a data mining system using Ptree-encoded vertical data representation to enable fast mining over large datasets. The vertical layout with Ptree processing boosts efficiency and scalability for association rule mining over row-based models. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Masum Serazi (North Dakota State University)
- 2. Vasily Malakhov (North Dakota State University)
- 3. Dongmei Ren (North Dakota State University)
- 4. Amal Perera (North Dakota State University)
- 5. Imad Rahal (North Dakota State University)
- 6. Weihua Wu (North Dakota State University)
- 7. Qiang Ding (North Dakota State University)
- 8. Fei Pan (North Dakota State University)
- 9. William Perrizo (North Dakota State University)
BibTeX Citation
@inproceedings{serazi_sigmod04,
title = {{DataMIME (Data: Mine It More Efficiently)}},
author = {Serazi, Masum and Malakhov, Vasily and Ren, Dongmei and Perera, Amal and Rahal, Imad and Wu, Weihua and Ding, Qiang and Pan, Fei and Perrizo, William},
series = {{SIGMOD} '04},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1007568.1007697},
url = {https://dl.acm.org/doi/10.1145/1007568.1007697},
year = {2004}
}
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 161 | Mining Frequent Patterns without Candidate Generation | 2000 | SIGMOD | 0.00027981772 |
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