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 88
... defined aggregates that provide a model, powerful and general as well, of the relevant aspects and tasks of knowledge discovery. Data Mining Query Language for Knowledge Discovery in a Geographical Information System presents SDMOQL a ...
... defined as a combination (boolean expression) of primitive constraints that have to be satisfied by the patterns ... define syntactical restrictions on desired patterns, e.g., its “length” is below a user-given threshold. Preprocessing ...
... definition of a pattern domain. Section 3 identifies several important open problems. Section 4 provides elements of ... defined and used. 2.1 Language of Patterns and Terminology We introduce some notations that are used for defining ...
... Definition 3 (Association Rules). An association rule is denoted X ⇒ Y where X ∩ Y = ∅ and X ⊆ Items is the body of the rule and Y ⊆ Items is the head of the rule. Let us now define constraints on itemsets. Definition 4 (Constraint) ...
... Definition 7 (Frequency). The absolute frequency of an itemset S in r is defined by Fa (S,r) = |support(S)| where |.| denote the cardinality of the multiset (each transaction is counted with its multiplicity). The relative frequency of ...
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 |