Classification.- Nonredundant Generalized Rules and Their Impact in Classification.- Asymmetric and Sample Size Sensitive Entropy Measures for Supervised Learning.- Algebra and Topology for Dominance-Based Rough Set Approach.- Approximation & Data Security.- Approximate Relational Reasoning by Stochastic Propositionalization.- LSA-Based Compression of Data Cubes for Efficient Approximate Range-SUM Query Answering in OLAP.- Security Requirements Engineering: The SI* Modeling Language and the Secure Tropos Methodology.- Privacy Protection for Genomic Data: Current Techniques and Challenges.- Knowledge Management.- Unifying the Concept of Collection in Digital Libraries.- Inferring User Goals from Sets of Independent Queries in a Multidatabase Environment.- The CPT Structure of Variable Elimination in Discrete Bayesian Networks.- Summaries of Action Rules by Agglomerative Clustering.- Applications.- Bar Charts in Popular Media: Conveying Their Message to Visually Impaired Users via Speech.- Conceptual Development of Mental Health Ontologies.- Multiple Classifiers for Different Features in Timbre Estimation.- Identification of Musical Instruments by Features Describing Sound Changes in Time.

Intelligent Information Systems (IIS) can be defined as the next generation of Information Systems (IS) developed as a result of integration of AI and database (DB) technologies. IIS embody knowledge that allows them to exhibit intelligent behavior, allows them to cooperate with users and other systems in problem solving, discovery, retrieval, and manipulation of data and knowledge. For any IIS to serve its purpose, the information must be available when it is needed. This means that the computing systems used to store data and process the information, and the security controls used to protect it must be functioning correctly. This book covers some of the above topics and it is divided into four sections: Classification, Approximation and Data Security, Knowledge Management, and Application of IIS to medical and music domains.