Database Support for Data Mining Applications: Discovering Knowledge with Inductive QueriesRosa Meo, Pier L. Lanzi, Mika Klemettinen Springer, 2004 M07 28 - 332 pages Data mining from traditional relational databases as well as from non-traditional ones such as semi-structured data, Web data, and scientific databases housing biological, linguistic, and sensor data has recently become a popular way of discovering hidden knowledge. This book on database support for data mining is developed to approaches exploiting the available database technology, declarative data mining, intelligent querying, and associated issues, such as optimization, indexing, query processing, languages, and constraints. Attention is also paid to the solution of data preprocessing problems, such as data cleaning, discretization, and sampling. The 16 reviewed full papers presented were carefully selected from various workshops and conferences to provide complete and competent coverage of the core issues. Some papers were developed within an EC funded project on discovering knowledge with inductive queries. |
From inside the book
Results 1-5 of 31
... version space of the solutions are proposed and experimented in the user-modeling domain. Support for Knowledge Discovery Process Interactivity, Scalability and Resource Control for Efficient KDD Support in DBMS proposes a new approach ...
... version-space representations that are important for their applicability to inductive databases. They correspond to the task of concept learning from a database of examples when this database is updated. One-sided instance-based ...
... space corresponds to the union of various version spaces [60,57,40,41]. Because each version space can be represented in a concise way using its border sets S and G, [30] shows that the solution space of a query can be represented using ...
... space is a version space. They are useful in case only membership of the solution set is important. – Closed sets [65,12], δ-free sets [15,16], and disjoint-free sets [25] are condensed representations that have been designed as ε ...
... version spaces (extended abstract). In Proceedings DTDM'02 co-located with ... space algorithm and its application to molecular fragment finding. In ... version appears in this volume. B. Goethals and J. V. den Bussche. On supporting ...
Contents
1 | |
24 | |
Declarative Data Mining Using SQL3 | 52 |
Towards a Logic Query Language for Data Mining | 76 |
A Data Mining Query Language for Knowledge Discovery in | 95 |
Towards Query Evaluation in Inductive Databases Using Version Spaces | 117 |
The GUHA Method Data Preprocessing and Mining | 135 |
Constraint Based Mining of First Order Sequences in SeqLog | 154 |
Frequent Itemset Discovery with SQL Using Universal Quantification | 194 |
Deducing Bounds on the Support of Itemsets | 214 |
ModelIndependent Bounding of the Supports of Boolean Formulae | 234 |
Condensed Representations for Sets of Mining Queries | 250 |
Arnaud Giacometti Dominique Laurent Cheikh Talibouya Diop | 270 |
Evgueni N Smirnov Ida G SprinkhuizenKuyper H Japp van den Herik | 289 |
Kimmo Hätönen Mika Klemettinen | 304 |
Artur Bykowski Thomas Daurel Nicolas Méger Christophe Rigotti | 324 |