出版社:Springer
ISBN:9783540224792
作者:Meo,Rosa
书籍目录
I Database Languages and Query Execution
Inductive Databases and Multiple Uses of Frequent Itemsets: the cINQ Approach
Query Languages Supporting Descriptive Rule Mining: A Comparative Study
Declarative Data Mining Using SQL3
Towards a Logic Query Language for Data Mining
A Data Mining Query Language for Knowledge Discovery in a
Towards Query Evaluation in Inductive Databases Using Version Spaces
The GUHA Method, Data Preprocessing and Mining
Constraint Based Mining of First Order Sequences in SeqLog
II Support for KDD-Process
Interactivity, Scalability and Resource Control for Efficient KDD Support in DBMS
Frequent Itemset Discovery with SQL Using Universal Quantification
Deducing Bounds on the Support of Itemsets
Model-Independent Bounding Of the Supports of Boolean Formulae in Binary Data
Condensed Representations for Sets of Mining Queries
One-Sided Instance-Based Boundary Sets
Domain tructures in Filtering irrelevant Frequent Patterns
Integrity Constraints over Association Rules
Author Index
作者简介
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.
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