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DEMON: Mining and Monitoring Evolving Data (2000)  (Make Corrections)  (17 citations)
Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishnan
Knowledge and Data Engineering



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Abstract: Data mining algorithms have been the focus of much research recently. In practice, the input data to a data mining process resides in a large data warehouse whose data is kept up-to-date through periodic or occasional addition and deletion of blocks of data. Most data mining algorithms have either assumed that the input data is static, or have been designed for arbitrary insertions and deletions of data records. In this paper, we consider a dynamic environment that evolves through systematic... (Update)

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BibTeX entry:   (Update)

Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishnan. "DEMON: Mining and Monitoring Evolving Data.", in ICDE 2000: 439-448, San Diego, CA. http://citeseer.ist.psu.edu/ganti00demon.html   More

@article{ ganti01demon,
    author = "Venkatesh Ganti and Johannes Gehrke and Raghu Ramakrishnan",
    title = "{DEMON}: Mining and Monitoring Evolving Data",
    journal = "Knowledge and Data Engineering",
    volume = "13",
    number = "1",
    pages = "50-63",
    year = "2001",
    url = "citeseer.ist.psu.edu/ganti00demon.html" }
Citations (may not include all citations):
910   Fast Algorithms for Mining Association Rules - Agrawal, Srikant - 1994
805   Algorithms for Clustering Data (context) - Jain, Dubes - 1988
475   Automatic subspace clustering of high dimensional data for d.. - Agrawal, Gehrke et al. - 1998
474   Advances in Knowledge Discovery and Data Mining (context) - Fayyad, Piatetsky-Shapiro et al. - 1996
400   Fast Discovery of Association Rules (context) - Agrawal, Mannila et al. - 1996
222   BIRCH: An efficient data clustering method for very large da.. - Zhang, Ramakrishnan et al. - 1996
106   Maintenance of discovered association rules in large databas.. - Cheung, Han et al.
102   Selection of views to materialize in a data warehouse - Gupta - 1997
46   A database interface for clustering in large spatial databas.. (context) - Ester, Kriegel et al. - 1995
44   Fast sequential and parallel algorithms for association rule.. - Mueller - 1995
37   BOAT-- optimistic decision tree construction - Gehrke, Ganti et al. - 1999
36   Incremental clustering for mining in a data warehousing envi.. - Ester, Kriegel et al. - 1998
35   Recent trends in hierarchical document clustering: A critica.. (context) - Willett - 1988
29   An efficient algorithm for the incremental updation of assoc.. - Thomas, Bodagala et al. - 1997
29   Efficient algorithms for discovering frequent sets in increm.. (context) - Feldman, Aumann et al. - 1997
19   ID5: An incremental ID (context) - Utgoff - 1988
10   An overview of data warehouse and olap technology (context) - Chaudhuri, Dayal - 1997
3   Integrating mining with relational databases: Alternatives a.. (context) - Sarawagi, Thomas et al. - 1998
3   Data organization for efficient mining (context) - Dunkel, Soparkar - 1999



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