DBMiner: A System for Mining Knowledge in Large Relational Databases

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DBMiner: A System for Mining Knowledge in Large Relational Databases (1996)

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by Jiawei Han , Yongjian Fu , Wei Wang , Jenny Chiang , Wan Gong , Krzysztof Koperski , Deyi Li , Yijun Lu , Amynmohamed Rajan , Nebojsa Stefanovic , Betty Xia , Osmar R. Zaiane

Venue:	In Proc. 1996 Int'l Conf. on Data Mining and Knowledge Discovery (KDD'96
Citations:	56 - 12 self

BibTeX

@INPROCEEDINGS{Han96dbminer:a,
    author = {Jiawei Han and Yongjian Fu and Wei Wang and Jenny Chiang and Wan Gong and Krzysztof Koperski and Deyi Li and Yijun Lu and Amynmohamed Rajan and Nebojsa Stefanovic and Betty Xia and Osmar R. Zaiane},
    title = {DBMiner: A System for Mining Knowledge in Large Relational Databases},
    booktitle = {In Proc. 1996 Int'l Conf. on Data Mining and Knowledge Discovery (KDD'96},
    year = {1996},
    pages = {250--255},
    publisher = {AAAI Press}
}

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Abstract

A data mining system, DBMiner, has been developed for interactive mining of multiple-level knowledge in large relational databases. The system implements a wide spectrum of data mining functions, including generalization, characterization, association, classi#- cation, and prediction. By incorporating several interesting data mining techniques, including attributeoriented induction, statistical analysis, progressive deepening for mining multiple-level knowledge, and meta-rule guided mining, the system provides a userfriendly, interactive data mining environment with good performance.

Keyphrases

large relational database multiple-level knowledge several interesting data mining technique interactive mining good performance classi cation interactive data mining environment data mining system data mining function wide spectrum progressive deepening statistical analysis

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