Advances in Data Management [electronic resource] /
Ras, Zbigniew W.editor.
Dardzinska, Agnieszka.editor.
Data Management is the process of planning, coordinating and controlling data resources. More often, applications need to store and search a large amount of data. Managing Data has been continuously challenged by demands from various areas and applications and has evolved in parallel with advances in hardware and computing techniques. This volume focuses on its recent advances and it is composed of five parts and a total of eighteen chapters. The first part of the book contains five contributions in the area of information retrieval & Web intelligence: a novel approach to solving index selection problem, integrated retrieval from Web of documents and data, bipolarity in database querying, deriving data summarization through ontologies, and granular computing for Web intelligence. The second part of the book contains four contributions in knowledge discovery area. Its third part contains three contributions in information integration & data security area. The remaining two parts of the book contain six contributions in the area of intelligent agents and applications of data management in medical domain.
Bibliographic Level Mode of Issuance: Monograph
Includes bibliographical references and index.
Information Retrieval and Web Intelligence -- Automatic Index Selection in RDBMS by Exploring Query Execution Plan Space -- Integrated Retrieval from Web of Documents and Data -- Bipolar Queries: A Way to Enhance the Flexibility of Database Queries -- On Deriving Data Summarization through Ontologies to Meet User Preferences -- Granular Computing for Web Intelligence -- Knowledge Discovery -- Visualizing High Dimensional Classifier Performance Data -- Extending Rule-Based Classifiers to Improve Recognition of Imbalanced Classes -- Converting between Various Sequence Representations -- Considerations on Logical Calculi for Dealing with Knowledge in Data Mining -- Information Integration and Data Security -- A Study on Recent Trends on Integration of Security Mechanisms -- Monitoring-Based Approach for Privacy Data Management -- Achieving Scalability with Schema-Less Databases -- Intelligent Agents -- Managing Pervasive Environments through Database Principles: A Survey -- Toward a Novel Design of Swarm Robots Based on the Dynamic Bayesian Network -- Current Research Trends in Possibilistic Logic: Multiple Agent Reasoning, Preference Representation, and Uncertain Databases -- Data Management in Medical Domain -- Atherosclerosis Risk Assessment Using Rule-Based Approach -- Interpretation of Imprecision in Medical Data -- Promoting Diversity in Top Hits for Biomedical Passage Retrieval.
Data Management is the process of planning, coordinating and controlling data resources. More often, applications need to store and search a large amount of data. Managing Data has been continuously challenged by demands from various areas and applications and has evolved in parallel with advances in hardware and computing techniques. This volume focuses on its recent advances and it is composed of five parts and a total of eighteen chapters. The first part of the book contains five contributions in the area of information retrieval & Web intelligence: a novel approach to solving index selection problem, integrated retrieval from Web of documents and data, bipolarity in database querying, deriving data summarization through ontologies, and granular computing for Web intelligence. The second part of the book contains four contributions in knowledge discovery area. Its third part contains three contributions in information integration & data security area. The remaining two parts of the book contain six contributions in the area of intelligent agents and applications of data management in medical domain.
Artificial intelligence.
Data structures (Computer science).
Applied mathematics.
Engineering mathematics.
Artificial Intelligence.
Data Structures and Information Theory.
Mathematical and Computational Engineering.
Studies in Computational Intelligence