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Foundations of Data Organization and Algorithms

Foundations of Data Organization and Algorithms PDF Author: David B. Lomet
Publisher:
ISBN: 9783662192245
Category :
Languages : en
Pages : 432

Book Description


Foundations of Data Organization and Algorithms

Foundations of Data Organization and Algorithms PDF Author: David B. Lomet
Publisher:
ISBN: 9783662192245
Category :
Languages : en
Pages : 432

Book Description


Foundations of Data Organization and Algorithms

Foundations of Data Organization and Algorithms PDF Author: Witold Litwin
Publisher:
ISBN: 9783662178188
Category :
Languages : en
Pages : 544

Book Description


Foundations of Data Organization and Algorithms

Foundations of Data Organization and Algorithms PDF Author: Witold Litwin
Publisher: Springer Science & Business Media
ISBN: 9783540512950
Category : Computers
Languages : en
Pages : 552

Book Description
The Third International Conference on Foundations of Data Organization and Algorithms has been organized by INRIA in Paris from June 21 to 23, 1989. Previous FODO Conferences were held in Warsaw, 1981, and in Kyoto, 1985. The goal of this year's conference is to present advances in techniques of permanent and temporary data organization in different fields. New applications such as image processing, graphics, geographic data processing, robotics, office automation, information systems, language translation, and expert systems have developed various data organizations and algorithms specific to the application requirements. The growing importance of these applications has created a need for general studies on data organization and algorithms as well as for specific studies on new database management systems and on filing services. The articles submitted for the conference were subject to the usual rigorous reviewing process and selected on that basis. They offer an excellent snapshot of the state of the art in the field and should prove invaluable for computer scientists faced by the problems of data organization which are raised by these new applications.

Foundations of Data Organization and Algorithms

Foundations of Data Organization and Algorithms PDF Author: David B. Lomet
Publisher: Springer Science & Business Media
ISBN: 9783540573012
Category : Computers
Languages : en
Pages : 430

Book Description
This volume presents the proceedings of the Fourth International Conference on Data Organization and Algorithms, FODO '93, held in Evanston, Illinois. FODO '93 reflects the maturing of the database field which hasbeen driven by the enormous growth in the range of applications for databasesystems. The "non-standard" applications of the not-so-distant past, such ashypertext, multimedia, and scientific and engineering databases, now provide some of the central motivation for the advances in hardware technology and data organizations and algorithms. The volume contains 3 invited talks, 22 contributed papers, and 2 panel papers. The contributed papers are grouped into parts on multimedia, access methods, text processing, query processing, industrial applications, physical storage, andnew directions.

Information Organization and Databases

Information Organization and Databases PDF Author: Katsumi Tanaka
Publisher: Springer Science & Business Media
ISBN: 1461513790
Category : Computers
Languages : en
Pages : 377

Book Description
Information Organization and Databases: Foundations of Data Organization provides recent developments of information organization technologies that have become crucial not only for data mining applications and information visualization, but also for treatment of semistructured data, spatio-temporal data and multimedia data that are not necessarily stored in conventional DBMSs. Information Organization and Databases: Foundations of Data Organization presents: semistructured data addressing XML, query languages and integrity constraints, focusing on advanced technologies for organizing web data for effective retrieval; multimedia database organization emphasizing video data organization and data structures for similarity retrieval; technologies for data mining and data warehousing; index organization and efficient query processing issues; spatial data access and indexing; organizing and retrieval of WWW and hypermedia. Information Organization and Databases: Foundations of Data Organization is a resource for database practitioners, database researchers, designers and administrators of multimedia information systems, and graduate-level students in the area of information retrieval and/or databases wishing to keep abreast of advances in the information organization technologies.

Foundations of Data Organization and Algorithms

Foundations of Data Organization and Algorithms PDF Author:
Publisher:
ISBN:
Category : Algorithms
Languages : en
Pages : 444

Book Description


Foundations of Data Organization

Foundations of Data Organization PDF Author: Sakti P. Ghosh
Publisher: Springer Science & Business Media
ISBN: 1461318815
Category : Science
Languages : en
Pages : 615

Book Description
Foundations of data organization is a relatively new field of research in comparison to, other branches of science. It is close to twenty years old. In this short life span of this branch of computer science, it has spread to all corners of the world, which is reflected in this book. This book covers new database application areas (databases for advanced applications and CAD/VLSI databases), computational geometry, file allocation & distributed databases, database models (including non traditional database models), database machines, query processing & physical structures for relational databases, besides traditional file organization (hashing, index file organization, mathematical file organization and consecutive retrieval property), in order to identify new trends of database research. The papers in this book originally represent talks given at the International Conference on Foundations of Data Organization, which was held on May 21-24, 1985, in Kyoto, Japan. This conference was held at Kyoto University, and sponsored by the organizing committee of the International Conference on Foundations of Data Organization and the Japan Society for the Promotion of Science. The conference was in cooperation with: ACM SIGMOD, IEEE Computer Society, Information Processing Society of Japan, IBM Research, Kyushu University, Kobe University, IBM Japan, Kyoto Sangyo University and Polish Academy of Sciences. This Conference was the follow-up of the first conference, which was hosted by the Polish Academy of Sciences and held at Warsaw in 1981. The Warsaw conference focused mainly on consecutive retrieval property and it's applications.

The Algorithmic Foundations of Differential Privacy

The Algorithmic Foundations of Differential Privacy PDF Author: Cynthia Dwork
Publisher:
ISBN: 9781601988188
Category : Computers
Languages : en
Pages : 286

Book Description
The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.

Foundations of Data Quality Management

Foundations of Data Quality Management PDF Author: Wenfei Fan
Publisher: Morgan & Claypool Publishers
ISBN: 160845777X
Category : Computers
Languages : en
Pages : 220

Book Description
Provides an overview of fundamental issues underlying central aspects of data quality - data consistency, data deduplication, data accuracy, data currency, and information completeness. The book promotes a uniform logical framework for dealing with these issues, based on data quality rules.

Foundations of Data Science

Foundations of Data Science PDF Author: Avrim Blum
Publisher: Cambridge University Press
ISBN: 1108617360
Category : Computers
Languages : en
Pages : 433

Book Description
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.