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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wei-Min Shen Bing Leng |
| Copyright Year | 1989 |
| Abstract | A metapattern (also known as a metaquery) is a new approach for integrated data mining systems. As opposed to a typical "toolbox"-like integration, where components must be picked and chosen by users without much help, metapatterns provide a common representation for inter-component communication as well as a human interface for hypothesis development and search control. One weakness of this approach, however, is that the task of generating fruitful metapatterns is still a heavy burden for human users. In this paper, we describe a metapattern generator and an integrated discovery loop that can automatically generate metapatterns. Experiments in both artificial and real-world databases have shown that this new system goes beyond the existing machine learning technologies, and can discover relational patterns without requiring humans to pre-label the data as positive or negative examples for some given target concepts. With this technology, future data mining systems could discover high-quality, human-comprehensible knowledge in a much more efficient and focused manner, and data mining could be managed easily by both expert and less-expert users. |
| Sponsorship | IEEE IEEE Comput. Soc. Tech. Committee on Data Eng IEEE Computer Society |
| Starting Page | 898 |
| Ending Page | 910 |
| Page Count | 13 |
| File Size | 1714341 |
| File Format | |
| ISSN | 10414347 |
| Volume Number | 8 |
| Issue Number | 6 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1996-12-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Unsupervised learning Humans Data mining Relational databases Machine learning Machine learning algorithms Data analysis Automatic control Communication system control Knowledge management |
| Content Type | Text |
| Resource Type | Article |
| Subject | Information Systems Computational Theory and Mathematics Computer Science Applications |
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