Databaseresearchisa?eldofcomputersciencewheretheorymeetsapplications. Many concepts and methods, that were regarded as issues of theoretical interest when initially proposed, are now included in implemented database systems and related products. Examples abound in the ?elds of database design, query languages, query optimization, concurrency control, statistical databases, and many others. The papers contained in this volume were presented at ICDT’99, the 7th - ternationalConferenceonDatabaseTheory,inJerusalem,Israel,January10–12, 1999. ICDT is an international forum for research on the principles of database systems. It is a biennial conference, and has a tradition of being held in beau- ful European sites: Rome in 1986, Bruges in 1988, Paris in 1990, Berlin in 1992, Prague in 1995, and Delphi in 1997. From 1992, ICDT has been merged with another series of conferences on theoretical aspects of database systems, The Symposium on Mathematical Fundamentals of Database Systems (MFDBS), that was initiated in Dresden (1987), and continued in Visegrad (1989) and Rostock (1991). ICDT aims to enhance the exchange of ideas and cooperation in database research both within uni?ed Europe, and between Europe and the other continents. ICDT’99 was organized in cooperation with: ACM Special Interest Group on Management of Data (Sigmod) IEEE Israel Chapter ILA — The Israel Association for Information Processing EDBT Foundation ICDT’99 was sponsored by: The Hebrew University of Jerusalem Tel Aviv University Tandem Labs Israel, a Compaq Company This volume contains 26 technical papers selected from 89 submissions.

This book constitutes the refereed proceedings of the 8th International Conference on Database Theory, ICDT 2001, held in London, UK, in January 2001. The 26 revised full papers presented together with two invited papers were carefully reviewed and selected from 75 submissions. All current issues on database theory and the foundations of database systems are addressed. Among the topics covered are database queries, SQL, information retrieval, database logic, database mining, constraint databases, transactions, algorithmic aspects, semi-structured data, data engineering, XML, term rewriting, clustering, etc.

This book constitutes the refereed proceedings of the 9th International Conference on Database Theory, ICDT 2002, held in Siena, Italy in January 2002. The 26 revised full papers presented together with 3 invited articles were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections on reasoning about XML schemas and queries, aggregate queries, query evaluation, query rewriting and reformulation, semistructured versus structured data, query containment, consistency and incompleteness, and data structures.

This book constitutes the refereed proceedings of the 10th International Conference on Database Theory, ICDT 2005, held in Edinburgh, UK in January 2005. The 24 revised full papers presented together with 3 invited articles were carefully reviewed and selected from 84 submissions. The papers are organized in topical sections on query languages and types, multi-dimensional data processing, algorithmic aspects, privacy and security, logic and databases, query rewriting, and query processing and data streams.

This book is a comprehensive presentation of entity-relationship (ER) modeling with regard to an integrated development and modeling of database applications. It comprehensively surveys the achievements of research in this field and deals with the ER model and its extensions. In addition, the book presents techniques for the translation of the ER model into classical database models and languages, such as relational, hierarchical, and network models and languages, as well as into object-oriented models.

This is the first comprehensive survey of the field of constraint databases, written by leading researchers. Constraint databases are a fairly new and active area of database research. Their ability to deal with infinite sets makes them particularly promising as a technology for integrating spatial and temporal data with standard relational databases. Constraint databases bring techniques from a variety of fields, such as logic and model theory, algebraic and computational geometry, as well as symbolic computation, to the design and analysis of data models and query languages.

This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.

This book constitutes the refereed proceedings of the 11th International Conference on Database Theory, ICDT 2007, held in Barcelona, Spain in January 2007. The 25 revised papers presented together with 3 invited papers were carefully reviewed and selected from 111 submissions. The papers are organized in topical sections on information integration and peer to peer, axiomatizations for XML, expressive power of query languages, incompleteness, inconsistency, and uncertainty, XML schemas and typechecking, stream processing and sequential query processing, ranking, XML update and query, as well as query containment.

Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.

Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.