Digital Symposium Collection 2000

Exploratory Mining via Constrained Frequent Set Queries Raymond T. Ng, Laks V. S. Lakshmanan, Jiawei Han, and Teresa Mah   View Paper (PDF)     View Demo (HTML)   Return to Demonstrations Abstract Although there have been many studies on data mining, to date there have been few research prototypes or commercial systems supporting comprehensive query-driven mining, which encourages interactive exploration of the data. Our thesis is that constraint constructs and the optimization they induce play a pivotal role in mining queries, thus substantially enhancing the usefulness and performance of the mining system. This is based on the analogy of declarative query languages like SQL and query optimization which have made relational databases so successful. To this end, our proposed demo is not yet another data mining system, but of a new paradigm in data mining with constraints, as the important first step towards supporting ad-hoc mining in DBMS. In this demo, we will show a prototype exploratory mining system that implements constraint-based mining query optimization methods proposed in [5]. We will demonstrate how a user can interact with the system for exploratory data mining and how efficiently the system may execute optimized data mining queries. The prototype system will include all the constraint pushing techniques for mining association rules outlined in [5], and will include additional capabilities for mining other kinds of rules for which the computation of constrained frequent sets forms the core first step. References Note: References link to DBLP on the Web. [1] Rakesh Agrawal , Tomasz Imielinski , Arun N. Swami : Mining Association Rules between Sets of Items in Large Databases. SIGMOD Conference 1993 : 207-216 [2] Sergey Brin , Rajeev Motwani , Craig Silverstein : Beyond Market Baskets: Generalizing Association Rules to Correlations. SIGMOD Conference 1997 : 265-276 [3] Surajit Chaudhuri : Data Mining and Database Systems: Where is the Intersection? Data Engineering Bulletin 21(1) : 4-8(1998) [4] Tomasz Imielinski , Heikki Mannila : A Database Perspective on Knowledge Discovery. CACM 39(11) : 58-64(1996) [5] Raymond T. Ng , Laks V. S. Lakshmanan , Jiawei Han , Alex Pang : Exploratory Mining and Pruning Optimizations of Constrained Association Rules. SIGMOD Conference 1998 : 13-24 [6] Sunita Sarawagi , Shiby Thomas , Rakesh Agrawal : Integrating Mining with Relational Database Systems: Alternatives and Implications. SIGMOD Conference 1998 : 343-354 [7] Abraham Silberschatz , Stanley B. Zdonik : Database Systems - Breaking Out of the Box. SIGMOD Record 26(3) : 36-50(1997) [8] Shalom Tsur , Jeffrey D. Ullman , Serge Abiteboul , Chris Clifton , Rajeev Motwani , Svetlozar Nestorov , Arnon Rosenthal : Query Flocks: A Generalization of Association-Rule Mining. SIGMOD Conference 1998 : 1-12 BIBTEX @inproceedings{DBLP:conf/sigmod/NgLHM99,   author    = {Raymond T. Ng and                 Laks V. S. Lakshmanan and                 Jiawei Han and                 Teresa Mah},    editor    = {Alex Delis and                 Christos Faloutsos and                 Shahram Ghandeharizadeh},    title     = {Exploratory Mining via Constrained Frequent Set Queries},    booktitle = {SIGMOD 1999, Proceedings ACM SIGMOD International Conference                 on Management of Data, June 1-3, 1999, Philadephia, Pennsylvania,                 USA},    publisher = {ACM Press},    year      = {1999},    isbn      = {1-58113-084-8},    pages     = {556-558},    crossref  = {DBLP:conf/sigmod/99},    bibsource = {DBLP, http://dblp.uni-trier.de} } }, Copyright(C) 2000 ACM