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SIGMOD/PODS '18: International Conference on Management of Data Jun 03, 2018-Jun 08, 2018 Houston, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Privacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area. Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference.
This book constitutes the refereed proceedings of the 14th International Conference on Information Security, ISC 2011, held in Xi'an, China, in October 2011. The 25 revised full papers were carefully reviewed and selected from 95 submissions. The papers are organized in topical sections on attacks; protocols; public-key cryptosystems; network security; software security; system security; database security; privacy; digital signatures.
The emergence of new paradigms for data management raises a variety of exciting challenges. An important goal of database theory is to answer these challenges by providing sound foundations for the development of the field. This volume contains the papers selected for the third International Conference on Database Theory, ICDT'90. The conferences in this series are held biannually in beautiful European cities, Rome in 1986 and Bruges in 1988 with proceedings published as volumes 234 and 326 in the same series. ICDT'90 was organized in Paris by the Institut National de Recherche en Informatique et Automatique. The conference features 2 invited presentations and 31 papers selected from 129 submissions. The papers describe original ideas and new results on the foundations of databases, knowledge bases, object-oriented databases, relational theory, transaction management, data structures and deductive databases. The volume offers a good overview of the state of the art and the current trends in database theory. It should be a valuable source of information for researchers interested in the field.
Probabilistic databases are databases where the value of some attributes or the presence of some records are uncertain and known only with some probability. Applications in many areas such as information extraction, RFID and scientific data management, data cleaning, data integration, and financial risk assessment produce large volumes of uncertain data, which are best modeled and processed by a probabilistic database. This book presents the state of the art in representation formalisms and query processing techniques for probabilistic data. It starts by discussing the basic principles for representing large probabilistic databases, by decomposing them into tuple-independent tables, block-independent-disjoint tables, or U-databases. Then it discusses two classes of techniques for query evaluation on probabilistic databases. In extensional query evaluation, the entire probabilistic inference can be pushed into the database engine and, therefore, processed as effectively as the evaluation of standard SQL queries. The relational queries that can be evaluated this way are called safe queries. In intensional query evaluation, the probabilistic inference is performed over a propositional formula called lineage expression: every relational query can be evaluated this way, but the data complexity dramatically depends on the query being evaluated, and can be #P-hard. The book also discusses some advanced topics in probabilistic data management such as top-k query processing, sequential probabilistic databases, indexing and materialized views, and Monte Carlo databases. Table of Contents: Overview / Data and Query Model / The Query Evaluation Problem / Extensional Query Evaluation / Intensional Query Evaluation / Advanced Techniques
The major theme of this book is Intelligent Agents. An agent is a hardware or software system that is autonomous, interactive with and reactive to its environment and other agents. An agent can also be pro-active in taking the initiative in goal-directed behaviour. Intelligent Agents are one of the most important and exciting areas of research and development in computer science today.