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Algorithms and Data Structures
This book constitutes the refereed proceedings of the 10th International Workshop on Algorithms and Data Structures, WADS 2007, held in Halifax, Canada, in August 2007. The papers present original research on the theory and application of algorithms and data structures in all areas, including combinatorics, computational geometry, databases, graphics, parallel and distributed computing.
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From Data to Decisions in Music Education Research
From Data to Decisions in Music Education Research provides a structured and hands-on approach to working with empirical data in the context of music education research. Using step-by-step tutorials with in-depth examples of music education data, this book draws upon concepts in data science and statistics to provide a comprehensive framework for working with a variety of data and solving data-driven problems.All of the skills presented here use the R programming language, a free, open-source statistical computing and graphics environment. Using R enables readers to refine their computational thinking abilities and data literacy skills while facilitating reproducibility, replication, and transparency of data analysis in the field. The book offers: A clear and comprehensive framework for thinking about data analysis processes in a music education context. An overview of common data structures and data types used in statistical programming and data analytics. Techniques for cleaning, preprocessing, manipulating, aggregating, and mining data in ways that facilitate organization and interpretation. Methods for summarizing and visualizing data to help identify structures, patterns, and trends within data sets. Detailed applications of descriptive, diagnostic, and predictive analytics processes. Step-by-step code for all concepts and analyses. Direct access to all data sets and R script files through the accompanying eResource.From Data to Decisions in Music Education Research offers a reference "cookbook" of code and programming recipes written with the graduate music education student in mind and breaks down data analysis processes and skills in an approachable fashion. It can be used across a wide range of graduate music education courses that rely on the application of empirical data analyses and will be useful to all music education scholars and professionals seeking to enhance their use of quantitative data.
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Introduction to Data Systems
Encompassing a broad range of forms and sources of data, this textbook introduces data systems through a progressive presentation. Introduction to Data Systems covers data acquisition starting with local files, then progresses to data acquired from relational databases, from REST APIs and through web scraping. It teaches data forms/formats from tidy data to relationally defined sets of tables to hierarchical structure like XML and JSON using data models to convey the structure, operations, and constraints of each data form.The starting point of the book is a foundation in Python programming found in introductory computer science classes or short courses on the language, and so does not require prerequisites of data structures, algorithms, or other courses. This makes the material accessible to students early in their educational career and equips them with understanding and skills that can be applied in computer science, data science/data analytics, and information technology programs as well as for internships and research experiences. This book is accessible to a wide variety of students. By drawing together content normally spread across upper level computer science courses, it offers a single source providing the essentials for data science practitioners. In our increasingly data-centric world, students from all domains will benefit from the “data-aptitude” built by the material in this book.
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Data Structures and Algorithm Analysis in Java
Data Structures and Algorithm Analysis in Java is an advanced algorithms book that fits between traditional CS2 and Algorithms Analysis courses. In the old ACM Curriculum Guidelines, this course was known as CS7. It is also suitable for a first-year graduate course in algorithm analysis As the speed and power of computers increases, so does the need for effective programming and algorithm analysis. By approaching these skills in tandem, Mark Allen Weiss teaches readers to develop well-constructed, maximally efficient programs in Java. Weiss clearly explains topics from binary heaps to sorting to NP-completeness, and dedicates a full chapter to amortized analysis and advanced data structures and their implementation. Figures and examples illustrating successive stages of algorithms contribute to Weiss' careful, rigorous and in-depth analysis of each type of algorithm. A logical organization of topics and full access to source code complement the text's coverage.
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Conceptual Structures for Knowledge Creation and Communication
This volume contains the proceedings of ICCS 2003, the 11th International C- ferenceonConceptualStructures. Thisconferenceseriescontinuestobethemain forum for the presentation and discussion of state-of-the-art research on conc- tualstructures. Thetheories,methodologies,andtechniquespresentedherehave grown considerably in scope in recent years. On the other hand, solid bridges spanning the boundaries between such diverse ?elds as Conceptual Graphs, F- mal Concept Analysis, and others are increasingly being built in our community. The theme of this year’s conference was “Conceptual Structures for Kno- edge Creation and Communication”. In our increasingly (Inter)networked world, the potential support of information technology for the creation and commu- cation of quality knowledge is almost boundless. However, in reality, many c- ceptual barriers prevent the use of this potential. The main problem is no longer in the technological infrastructure, but in how to navigate, use, and manage the wealth of available data resources. Thus, the question is: how to create and communicate from data the information and ultimately the knowledge required by an ever more complex and dynamic society? Conceptual structures research focuses on what is behind and between the data glut and the information ov- load that need to be overcome in answering this question. In this way, our ?eld contributes important ideas on how to actually realize some of the many still ambitious visions. All regular papers were reviewed in a thorough and open process by at least two reviewers and one editor.
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People and Data
Organizational data can be one of the most valuable assets in a business. However, too often an organization's structure prevents the effective analysis of this data. This book solves that problem. People and Data is a practical guide for Organization Development (OD) professionals which explains how to structure an organization so that the business can collect data that is accurate, useful and impactful. This is the foundation of achieving valuable insights from organizational data. This book is full of practical tips and advice on how to design an organization where data is accessible to the whole workforce and not just kept in silos by those with data in their job title. This book also explains how to build data into the design of company culture as well as into workforce design, learning and development (L&D) and talent management initiatives. Finally, People and Data includes a toolkit with eight specific tools that can be used to build a better organization for data. Full of practical advice, key takeaways and real-world examples from companies including AT&T, Shell and J.P. Morgan this book is essential reading for all Organization Development (OD) professionals needing to ensure that their organization is structured to achieve the performance gains made possible by data and analytics.
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Algorithms and Data Structures
The papers in this volume were presented at the Seventh Workshop on Al- rithms and Data Structures (WADS 2001). The workshop took place August 8-10, 2001 in Providence, Rhode Island, USA. The workshop alternates with the Scandinavian Workshop on Algorithms Theory (SWAT), continuing the t- dition of SWAT and WADS starting with SWAT '88 and WADS '89. In response to the call for papers, 89 papers were submitted. From these submissions, the program committee selected 40 papers for presentation at the workshop. In addition invited plenary lectures were given by the following - stinguished researchers: Mikhail J. Atallah, F. Thomson Leighton, and Mihalis Yannakakis. On behalf of the program committee, we would like to express our apprec- tion to the invited speakers and to all the authors who submitted papers. August 2001 Frank Dehne J.. org-Rudiger .. Sack Roberto Tamassia Organization Conference Chair Roberto Tamassia (Brown) Program Committee Chairs Frank Dehne (Carleton) J.. org-Rudiger .. Sack (Carleton) Roberto Tamassia (Brown) Program Committee Alberto Apostolico (Purdue, Padova) Giuseppe Liotta (Perugia) Timothy Chan (Waterloo) Ernst W. Mayr (Munc .. hen) Bruno Codenotti (IMC) Joseph S.B. Mitchell (SUNY) Giuseppe Di Battista (Roma Tre) Stefan N.. aher (Trier) Shlomi Dolev (Ben-Gurion) Takao Nishizeki (Tohoku) Martin Farach-Colton Viktor K. Prasanna (USC) (Rutgers, Google) Enrico Puppo (Genova) Pierre Fraigniaud (LRI) Jose Rolim (Geneva) Harold N. Gabow (Colorado) Jack Snoeyink (UNC) Sally A. Goldman (Washington) Ioannis G. Tollis (UTD) Michael T.
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Practical Graph Structures in SQL Server and Azure SQL
Use the graph table features in Azure SQL that were introduced in SQL Server 2017 and further refined in SQL Server 2019. This book shows you how to create data structures to capture complex connections between items in your data. These connections will help you analyze and draw insights from connections in your data that go beyond classic relationships. The graph examples in the book are useful for analyzing social media relationships, complex product-to-customer relationships, and any other type of data analysis in which indirect connections that otherwise might be missed using conventional techniques can be mined for their insight and business value. Tree structures are covered, with emphasis on a structure commonly used by organizations to aggregate data at different levels of an organization. The book provides code examples of SQL Graph objects as well as an alternate tree implementation technique. Included is sample data (and data generators) for you to test for performance and choose the implementation approach that best suits your needs and that of your application.If your job involves analyzing or storage of data elements that are connected in a networked topology, then this is the book that will help you bring the power of SQL Server to bear on that data and take advantage of your existing knowledge. What You Will LearnUnderstand the graph model and the associated terms used in graph analysisStore highly connected data in SQL Server and Azure SQL alongside existing relational dataMake full use of the graph table feature that is refined and enhanced in SQL Server 2019Implement high performance tree structures that will make storing and querying tree data possibleReport on data associated with a tree structure to aggregate results at different levelsWho This Book Is For
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New Data Structures and Algorithms for Logic Synthesis and Verification
This book introduces new logic primitives for electronic design automation tools. The author approaches fundamental EDA problems from a different, unconventional perspective, in order to demonstrate the key role of rethinking EDA solutions in overcoming technological limitations of present and future technologies. The author discusses techniques that improve the efficiency of logic representation, manipulation and optimization tasks by taking advantage of majority and biconditional logic primitives. Readers will be enabled to accelerate formal methods by studying core properties of logic circuits and developing new frameworks for logic reasoning engines.
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Algebraic Approach to Data Processing
The book explores a new general approach to selecting—and designing—data processing techniques. Symmetry and invariance ideas behind this algebraic approach have been successful in physics, where many new theories are formulated in symmetry terms.The book explains this approach and expands it to new application areas ranging from engineering, medicine, education to social sciences. In many cases, this approach leads to optimal techniques and optimal solutions. That the same data processing techniques help us better analyze wooden structures, lung dysfunctions, and deep learning algorithms is a good indication that these techniques can be used in many other applications as well. The book is recommended to researchers and practitioners who need to select a data processing technique—or who want to design a new technique when the existing techniques do not work. It is also recommended to students who want to learn the state-of-the-art data processing.
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Data Mining Algorithms in C++
Discover hidden relationships among the variables in your data, and learn how to exploit these relationships. This book presents a collection of data-mining algorithms that are effective in a wide variety of prediction and classification applications. All algorithms include an intuitive explanation of operation, essential equations, references to more rigorous theory, and commented C++ source code.Many of these techniques are recent developments, still not in widespread use. Others are standard algorithms given a fresh look. In every case, the focus is on practical applicability, with all code written in such a way that it can easily be included into any program. The Windows-based DATAMINE program lets you experiment with the techniques before incorporating them into your own work.What You'll LearnUse Monte-Carlo permutation tests to provide statistically sound assessments of relationships present in your dataDiscover how combinatorially symmetric cross validation reveals whether your model has true power or has just learned noise by overfitting the dataWork with feature weighting as regularized energy-based learning to rank variables according to their predictive power when there is too little data for traditional methodsSee how the eigenstructure of a dataset enables clustering of variables into groups that exist only within meaningful subspaces of the dataPlot regions of the variable space where there is disagreement between marginal and actual densities, or where contribution to mutual information is highWho This Book Is ForAnyone interested in discovering and exploiting relationships among variables. Although all code examples are written in C++, the algorithms are described in sufficient detail that they can easily be programmed in any language.
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Computational Modelling of Concrete and Concrete Structures
Computational Modelling of Concrete and Concrete Structures contains the contributions to the EURO-C 2026 conference (March 9-12, 2026, Seefeld in Tirol, Austria).The papers review and discuss research advancements and assess the applicability and robustness of methods and models for the analysis and design of concrete, fibre-reinforced, and prestressed concrete structures, as well as masonry structures. Recent developments encompass data-driven approaches, artificial intelligence, and machine learning methods, as well as novel discretization techniques, probabilistic models, and an increasing focus on microstructural aspects in a multi-scale and multi-physics context. Additionally, there is a noticeable trend towards material-scale innovations, including the use of more eco-efficient binders, new fibres, and 3D-printable concretes, along with life-cycle-oriented models that address the aging and durability of both new and existing concrete infrastructure.Overall computational robustness, mathematical and mechanical rigour, and the quality of predictions and have further increased, accompanied by careful model validation based on respective experimental programmes. The book will serve as an important reference for both academics and professionals, stimulating new research directions in the field of computational modelling of concrete and its application to the analysis of concrete structures.EURO-C 2026 is the ninth edition of the EURO-C conference series after Innsbruck 1994, Bad Gastein 1998, St. Johann im Pongau 2003, Mayrhofen 2006, Schladming 2010, St. Anton am Arlberg 2014, Bad Hofgastein 2018, and Vienna 2022. The overarching focus of the conferences is on computational methods and numerical models for the analysis of concrete and concrete structures.
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Parallel Programming Using C++
Foreword by Bjarne Stroustrup Software is generally acknowledged to be the single greatest obstacle preventing mainstream adoption of massively-parallel computing. While sequential applications are routinely ported to platforms ranging from PCs to mainframes, most parallel programs only ever run on one type of machine. One reason for this is that most parallel programming systems have failed to insulate their users from the architectures of the machines on which they have run. Those that have been platform-independent have usually also had poor performance. Many researchers now believe that object-oriented languages may offer a solution. By hiding the architecture-specific constructs required for high performance inside platform-independent abstractions, parallel object-oriented programming systems may be able to combine the speed of massively-parallel computing with the comfort of sequential programming. Parallel Programming Using C++ describes fifteen parallel programming systems based on C++, the most popular object-oriented language of today. These systems cover the whole spectrum of parallel programming paradigms, from data parallelism through dataflow and distributed shared memory to message-passing control parallelism. For the parallel programming community, a common parallel application is discussed in each chapter, as part of the description of the system itself. By comparing the implementations of the polygon overlay problem in each system, the reader can get a better sense of their expressiveness and functionality for a common problem. For the systems community, the chapters contain a discussion of the implementation of the various compilers and runtime systems. In addition to discussing the performance of polygon overlay, several of the contributors also discuss the performance of other, more substantial, applications. For the research community, the contributors discuss the motivations for and philosophy of their systems. As well, many of the chapters include critiques that complete the research arc by pointing out possible future research directions. Finally, for the object-oriented community, there are many examples of how encapsulation, inheritance, and polymorphism can be used to control the complexity of developing, debugging, and tuning parallel software.
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Computer–Based Structure Elucidation from Spectral Data
Here, the authors introduce readers to solving molecular structure elucidation problems using the expert system ACD/Structure Elucidator. They explain in detail the concepts of the Computer-Assisted Structure Elucidation (CASE) approach and point out the crucial role of understanding the axiomatic nature of the data used to deduce the structure. Aspects covered include the main blocks of the expert system and essential features of the mathematical algorithms used. Graduate and PhD students as well as practicing chemists are provided with a detailed explanation of the various practical approaches depending on available spectral data peculiarities and the complexity of the unknown structure. This is supported by a large number of real-world completed examples, most of which are related to the structure elucidation of natural product molecules containing unusual skeletons. Dedicated software and further supplementary material are available at www.acdlabs.com/TeachingSE.
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Algebraic Approach to Data Processing
The book explores a new general approach to selecting—and designing—data processing techniques. Symmetry and invariance ideas behind this algebraic approach have been successful in physics, where many new theories are formulated in symmetry terms.The book explains this approach and expands it to new application areas ranging from engineering, medicine, education to social sciences. In many cases, this approach leads to optimal techniques and optimal solutions. That the same data processing techniques help us better analyze wooden structures, lung dysfunctions, and deep learning algorithms is a good indication that these techniques can be used in many other applications as well. The book is recommended to researchers and practitioners who need to select a data processing technique—or who want to design a new technique when the existing techniques do not work. It is also recommended to students who want to learn the state-of-the-art data processing.
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Assigning Structures to Ions in Mass Spectrometry
Summarizing our present knowledge of the structures and chemistry of small organic cations in the gas phase, Assigning Structures to Ions in Mass Spectrometry presents the methods necessary for determining gas-phase ion structures. It is a comprehensive resource of background material that is essential for the interpretation and understanding of organic mass spectra.Following a historical introduction of chief discoveries, the book surveys current experimental methods for ion production and separation as well as those designed to reveal qualitative and quantitative aspects of gas-phase ions. It also examines the computational chemistry and theoretical calculations that provide complementary thermochemical, structural, and mechanistic information. Five selected case studies illustrate specific challenges associated with ion structure assignment and thermochemical problems. The last major section of the book contains the data for describing or identifying all ions containing C alone and C with H, O, N, S, P, halogens, and small organic cations. Presenting material written by leading researchers in the field, Assigning Structures to Ions in Mass Spectrometry underscores the importance of understanding the behavior of small organic ions and gas-phase ion chemistry for making new ion structure assignments
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Algorithms and Data Structures
This book contains the papers presented at the 1989 Workshop on Algorithms and Data Structures, which succeeds the 1988 Scandinavian Workshop on Algorithm Theory. It presents current research in various areas of algorithms, computational geometry, geometric searching, VLSI placement and routing, graph algorithms, parallel algorithms, distributed algorithms, databases, and text searching.
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Compressed Data Structures for Strings
Data compression is mandatory to manage massive datasets, indexing is fundamental to query them. However, their goals appear as counterposed: the former aims at minimizing data redundancies, whereas the latter augments the dataset with auxiliary information to speed up the query resolution. In this monograph we introduce solutions that overcome this dichotomy. We start by presenting the use of optimization techniques to improve the compression of classical data compression algorithms, then we move to the design of compressed data structures providing fast random access or efficient pattern matching queries on the compressed dataset. These theoretical studies are supported by experimental evidences of their impact in practical scenarios.
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Data Structure in Cognitive Metaphor Research
This collection of papers focuses on cognitive metaphor research (CMR) from the perspective of the current debate on linguistic data and evidence. The peculiarity of the book is that it reveals the causes that trigger the methodological problems of data handling in CMR. These problems include the identifiability of metaphors in discourse and the reliability of the methods of gathering metaphors such as linguistic intuition, discourse analysis, corpus analysis, and psycholinguistic experiments. In order to overcome their weaknesses and to enhance their reliance, the papers argue, on the one hand, for the combination of different methods of gathering and evaluating data in CMR. On the other hand, the papers also point out that converging evidence cannot be obtained without constraining the combinability of data stemming from different sources.
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Algorithms and Data Structures
This book constitutes the refereed proceedings of the 15th Algorithms and Data Structures Symposium, WADS 2017, held in St. John's, NL, Canada, in July/August 2017. The 49 full papers presented together with 3 abstracts of invited talks were carefully reviewed and selected from 109 submissions. They present original research on the theory and application of algorithms and data structures in many areas, including combinatorics, computational geometry, databases, graphics, and parallel and distributed computing.The WADS Symposium, which alternates with the Scandinavian Symposium and Workshops on Algorithm Theory, SWAT, is intended as a forum for researchers in the area of design and analysis of algorithms and data structures. Papers presenting original research on the theory and application of algorithms and data structures
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Algorithms and Data Structures
The refereed proceedings of the 8th International Workshop on Algorithms and Data Structures, WADS 2003, held in Ottawa, Ontario, Canada, in July/August 2003.The 40 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 126 submissions. A broad variety of current aspects in algorithmics and data structures is addressed.
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OpenVMS Alpha Internals and Data Structures
OpenVMS Alpha Internals and Data Structures: Memory Management is an updateto selected parts of the book OpenVMS AXP Internals and Data Structures Version 1.5 (Digital Press, 1994). This book covers the extensions to the memory management subsystem of OpenVMS Alpha to allow the operating system and applications to access 64 bits of address space. It emphasizes system data structures and their manipulation by paging and swapping routines and related system services.It also describes management of dynamic memory, such as nonpaged pool, and support for nonuniform memory access (NUMA) platforms.This book is intended for systems programmers, technical consultants, application designers, and other computer progressions interested in learning the details of the OpenVMS executive. Teachers and students of graduate and advanced undergraduate courses in operating systems will find this book a valuable study in how theory and practice are resolved in a complex commercialoperating system.
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Introduction to Optimization of Structures
to Optimization of Structures With 66 Illustrations Springer-Verlag New York Berlin Heidelberg London Paris Tokyo Hong Kong N.V. Banichuk Institute for Problems in Mechanics USSR Academy of ScienCes 117526 Moscow Soviet Union Translator Vadim Komkov Mathematics and Computer Science Department Air Force Institute of Technology Wright Patterson Air Force Base, OH 45433 USA Original Russian edition Vvedenie v Optimizatsiyu Konstruktsiy published (c) 1986 by Nauka Moscow. Library of Congress Cataloging-in-Publication Data Banichuk, Nikolai Vladimirovich. [Vvedenie v optimizatsiiii konstruktsii. English] Introduction to optimization of structuresfN.V. Banichuk. p. cm. Translation of: Vvedenie v optimizaiSiiu konstrukiSii. Includes bibliographical references. ISBN-13:978-1-4612-7988-4 (aIk. paper) 1. Structures, Theory of. I. Title. TA645.B3513 1990 624. 1 '7-dc20 89-26165 Printed on acid-free paper. (c) 1990 Springer-Verlag New York, Inc. Softcover reprint of the hardcover 1st edition 1990 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer-Verlag New York, Inc.,175 Fifth Avenue, Ne\l York, NY 10010, USA), except for brief excerpts in connection with reviews or scholarly analysis Use in connection with any form of information storage and retrieval, electronic adaptation computer software, or by similar or dissimilar methodology now known or hereafter developec is forbidden.
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Index Data Structures in Object-Oriented Databases
Object-oriented database management systems (OODBMS) are used to imple ment and maintain large object databases on persistent storage. Regardless whether the underlying database model follows the object-oriented, the rela tional or the object-relational paradigm, a key feature of any DBMS product is content based access to data sets. On the one hand this feature provides user-friendly query interfaces based on predicates to describe the desired data. On the other hand it poses challenging questions regarding DBMS design and implementation as well as the application development process on top of the DBMS. The reason for the latter is that the actual query performance depends on a technically meaningful use of access support mechanisms. In particular, if chosen and applied properly, such a mechanism speeds up the execution of predicate based queries. In the object-oriented world, such queries may involve arbitrarily complex terms referring to inheritance hierarchies and aggregation paths. These features are attractive at the application level, however, they increase the complexity of appropriate access support mechanisms which are known to be technically non-trivial in the relational world.
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Mining of Data with Complex Structures
Mining of Data with Complex Structures:- Clarifies the type and nature of data with complex structure including sequences, trees and graphs- Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining.- Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints.- Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.)- Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees.- Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees.- Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach.- Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies.- Details the extension of the TMG framework for sequence mining- Provides an overview of the future research direction with respect to technical extensions and application areasThe primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.
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Index Data Structures in Object-Oriented Databases
Object-oriented database management systems (OODBMS) are used to imple ment and maintain large object databases on persistent storage. Regardless whether the underlying database model follows the object-oriented, the rela tional or the object-relational paradigm, a key feature of any DBMS product is content based access to data sets. On the one hand this feature provides user-friendly query interfaces based on predicates to describe the desired data. On the other hand it poses challenging questions regarding DBMS design and implementation as well as the application development process on top of the DBMS. The reason for the latter is that the actual query performance depends on a technically meaningful use of access support mechanisms. In particular, if chosen and applied properly, such a mechanism speeds up the execution of predicate based queries. In the object-oriented world, such queries may involve arbitrarily complex terms referring to inheritance hierarchies and aggregation paths. These features are attractive at the application level, however, they increase the complexity of appropriate access support mechanisms which are known to be technically non-trivial in the relational world.
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Algorithms and Data Structures
This volume contains the papers presented at the 11th Algorithms and Data Structures Symposium, WADS 2009 (formerly Workshop on Algorithms and Data Structures), held during August 21-23, 2009 in Ban?, Alberta, Canada. WADS alternates with the Scandinavian Workshop on Algorithms Theory (SWAT), continuing the tradition of SWAT and WADS starting with SWAT 1988 and WADS 1989. Inresponsetothecallforpapers,126papersweresubmitted. Fromtheses- missions, the ProgramCommittee selected 49 papers for presentation at WADS 2009. In addition, invited lectures were given by the following distinguished researchers: Erik Demaine, Richard Karp, and Christos Papadimitriou. On behalf of the Program Committee, we would like to express our appre- ation to the invited speakers, reviewers and all authors who submitted papers. May 2009 Frank Dehne Marina Gavrilova J.. org-Ru ..diger Sack Csaba D. T' oth Conference Organization Program Chairs Frank Dehne Marina Gavrilova Joerg-Ruediger Sack Csaba D.Toth Program Committee Sergei Bereg Allan Borodin Gerth Stolting Brodal Timothy Chan Mark de Berg Frank Devai Matt Duckham Rolf Fagerberg Randolph Franklin Joachim Gudmundsson Susanne Hambrusch Rolf Klein Mike Langston Ming Li Friedhelm Meyer auf der Heide Ian Munro Jon Rokne Shashi Shekhar Bettina Speckmann Paul Spirakis Gabor Tardos Je? Vitter Frances F. Yao Local Organization Marina Gavrilova Csaba D. Toth Jon Rokne Maruf Monwar Kushan Ahmadian Table of Contents On the Power of the Semi-Separated Pair Decomposition...1 Mohammad Ali Abam, Paz Carmi, Mohammad Farshi, and Michiel Smid Plane Graphs with Parity Constraints...
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Algorithms and Data Structures
This book constitutes the refereed proceedings of the 14th Algorithms and Data Structures Symposium, WADS 2015, held in Victoria, BC, Canada, August 2015. The 54 revised full papers presented in this volume were carefully reviewed and selected from 148 submissions. The Algorithms and Data Structures Symposium - WADS (formerly Workshop on Algorithms And Data Structures), which alternates with the Scandinavian Workshop on Algorithm Theory, is intended as a forum for researchers in the area of design and analysis of algorithms and data structures. WADS includes papers presenting original research on algorithms and data structures in all areas, including bioinformatics, combinatorics, computational geometry, databases, graphics, and parallel and distributed computing.
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Linguistic Structure Prediction
A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. We also survey natural language processing problems to which these methods are being applied, and we address related topics in probabilistic inference, optimization, and experimental methodology. Table of Contents: Representations and Linguistic Data / Decoding: Making Predictions / Learning Structure from Annotated Data / Learning Structure from Incomplete Data / Beyond Decoding: Inference
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Morphological Structure, Lexical Representation and Lexical Access (RLE Linguistics C: Applied Linguistics)
The main concern of this work is whether morphemes play a role in the lexical representation and processing of several types of polymorphemic words and, more particularly, at what precise representational and processing level. The book comprises two theoretical contributions and a number of empirical ones. One theoretical paper discusses several possible motivations for a morphologically organised mental lexicon (like the economy of representation view, and the efficiency of processing view), and lays out the weaknesses that are associated with some of these motivations. The other theoretical paper offers an interactive-activation reinterpretation of the findings that were originally reported within the lexical search framework. The empirical papers together cover a relatively broad array of language types and mainly deal with visual word recognition in normals in the context of lexical morphology (derived and compound words). Evidence is reported on the function of stems and affixes as processing units in prefixed and suffixed derivations. The role of semantic transparency in the lexical representation of compounds is studied, as is the effect of orthographic ambiguity on the parsing of novel compounds. The inflection-derivational distinction is approached in the context of Finnish, a highly agglutinative language with much richer morphology than the languages usually studied in psycholinguistic experiments on polymorphemic words. Two other contributions also approach the study object in the context of relatively uncharted domains: one presents data on Chinese, a language which uses a different script-type (logographic) from the languages that are usually studied (alphabetic script), and another one presents data on language production.
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Healthcare Data Analytics
At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available to solve healthcare problems.The book details novel techniques for acquiring, handling, retrieving, and making best use of healthcare data. It analyzes recent developments in healthcare computing and discusses emerging technologies that can help improve the health and well-being of patients.Written by prominent researchers and experts working in the healthcare domain, the book sheds light on many of the computational challenges in the field of medical informatics. Each chapter in the book is structured as a "survey-style" article discussing the prominent research issues and the advances made on that research topic. The book is divided into three major categories: Healthcare Data Sources and Basic Analytics - details the various healthcare data sources and analytical techniques used in the processing and analysis of such data Advanced Data Analytics for Healthcare - covers advanced analytical methods, including clinical prediction models, temporal pattern mining methods, and visual analytics Applications and Practical Systems for Healthcare - covers the applications of data analytics to pervasive healthcare, fraud detection, and drug discovery along with systems for medical imaging and decision supportComputer scientists are usually not trained in domain-specific medical concepts, whereas medical practitioners and researchers have limited exposure to the data analytics area. The contents of this book will help to bring together these diverse communities by carefully and comprehensively discussing the most relevant contributions from each domain.
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Algorithms and Data Structures
This book constitutes the refereed proceedings of the 5th International Workshop on Algorithms and Data Structures, WADS'97, held in Nova Scotia, Halifax, Canada, in August 1997.The 37 revised full papers presented were carefully selected from a total of 81 submissions. Also included are four abstracts and one full contribution corresponding to the invited talks. Among the topics covered are data structures and algorithmic aspects in a variety of areas like computational geometry, graph theory, networking, load balancing, optimization, approximation, sorting, pattern matching, etc.
R 1,587.07
R 1,678.00
Concept Data Analysis
With the advent of the Web along with the unprecedented amount of information available in electronic format, conceptual data analysis is more useful and practical than ever, because this technology addresses important limitations of the systems that currently support users in their quest for information. Concept Data Analysis: Theory & Applications is the first book that provides a comprehensive treatment of the full range of algorithms available for conceptual data analysis, spanning creation, maintenance, display and manipulation of concept lattices. The accompanying website allows you to gain a greater understanding of the principles covered in the book through actively working on the topics discussed. The three main areas explored are interactive mining of documents or collections of documents (including Web documents), automatic text ranking, and rule mining from structured data. The potentials of conceptual data analysis in the application areas being considered are further illustrated by two detailed case studies. Concept Data Analysis: Theory & Applications is essential for researchers active in information processing and management and industry practitioners who are interested in creating a commercial product for conceptual data analysis or developing content management applications.
R 4,557.00
Computer Analysis of Skeletal Structures
This book presents five computer programs in FORTRAN together with descriptions of how to use them for static analysis of skeletal structures. It includes several worked examples, including pin-jointed plane and space trusses, continuous beams, and two and three dimensional rigid-jointed frames.
R 13,872.61
Managing and Mining Uncertain Data
Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way. This book is organized to make it more accessible to applications-driven practitioners for solving real problems. Also, given the lack of structurally organized information on this topic, Managing and Mining Uncertain Data provides insights which are not easily accessible elsewhere. Managing and Mining Uncertain Data is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level students in computer science and engineering, as well as the ACM, IEEE, SIAM, INFORMS and AAAI Society groups.
R 4,418.84
