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Sequence Data Mining

Sequence Data Mining PDF Author: Guozhu Dong
Publisher: Springer Science & Business Media
ISBN: 0387699376
Category : Computers
Languages : en
Pages : 160

Book Description
Understanding sequence data, and the ability to utilize this hidden knowledge, will create a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more. This book provides thorough coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods. It offers balanced coverage on data mining and sequence data analysis, allowing readers to access the state-of-the-art results in one place.

Sequence Data Mining

Sequence Data Mining PDF Author: Guozhu Dong
Publisher: Springer Science & Business Media
ISBN: 0387699376
Category : Computers
Languages : en
Pages : 160

Book Description
Understanding sequence data, and the ability to utilize this hidden knowledge, will create a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more. This book provides thorough coverage of the existing results on sequence data mining as well as pattern types and associated pattern mining methods. It offers balanced coverage on data mining and sequence data analysis, allowing readers to access the state-of-the-art results in one place.

Pattern Discovery Using Sequence Data Mining

Pattern Discovery Using Sequence Data Mining PDF Author: Pradeep Kumar
Publisher:
ISBN: 9781613500583
Category : Sequential pattern mining
Languages : en
Pages : 272

Book Description
"This book provides a comprehensive view of sequence mining techniques, and present current research and case studies in Pattern Discovery in Sequential data authored by researchers and practitioners"--

Data Mining in Bioinformatics

Data Mining in Bioinformatics PDF Author: Jason T. L. Wang
Publisher: Springer Science & Business Media
ISBN: 9781852336714
Category : Computers
Languages : en
Pages : 356

Book Description
Written especially for computer scientists, all necessary biology is explained. Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.

Biological Sequence Analysis

Biological Sequence Analysis PDF Author: Richard Durbin
Publisher: Cambridge University Press
ISBN: 113945739X
Category : Science
Languages : en
Pages : 372

Book Description
Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques PDF Author: Jiawei Han
Publisher: Elsevier
ISBN: 0123814804
Category : Computers
Languages : en
Pages : 740

Book Description
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Sequence Analysis and Related Approaches

Sequence Analysis and Related Approaches PDF Author: Matthias Studer
Publisher:
ISBN: 9781013273841
Category : Social Science
Languages : en
Pages : 298

Book Description
This open access book provides innovative methods and original applications of sequence analysis (SA) and related methods for analysing longitudinal data describing life trajectories such as professional careers, family paths, the succession of health statuses, or the time use. The applications as well as the methodological contributions proposed in this book pay special attention to the combined use of SA and other methods for longitudinal data such as event history analysis, Markov modelling, and sequence network. The methodological contributions in this book include among others original propositions for measuring the precarity of work trajectories, Markov-based methods for clustering sequences, fuzzy and monothetic clustering of sequences, network-based SA, joint use of SA and hidden Markov models, and of SA and survival models. The applications cover the comparison of gendered occupational trajectories in Germany, the study of the changes in women market participation in Denmark, the study of typical day of dual-earner couples in Italy, of mobility patterns in Togo, of internet addiction in Switzerland, and of the quality of employment career after a first unemployment spell. As such this book provides a wealth of information for social scientists interested in quantitative life course analysis, and all those working in sociology, demography, economics, health, psychology, social policy, and statistics.; Provides new perspectives and methods for sequence analysis Focusses on the link between sequence analysis and other methods for longitudinal data, especially event history analysis and Markov models Stresses the complementarity of sequence analysis and other models for longitudinal data Applications of sequence analysis in a whole range of different domains This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Advances in Database Technology EDBT '96

Advances in Database Technology EDBT '96 PDF Author: Peter Apers
Publisher: Springer
ISBN: 9783540610571
Category : Computers
Languages : en
Pages : 646

Book Description
This book presents the refereed proceedings of the Fifth International Conference on Extending Database Technology, EDBT'96, held in Avignon, France in March 1996. The 31 full revised papers included were selected from a total of 178 submissions; also included are some industrial-track papers, contributed by partners of several ESPRIT projects. The volume is organized in topical sections on data mining, active databases, design tools, advanced DBMS, optimization, warehousing, system issues, temporal databases, the web and hypermedia, performance, workflow management, database design, and parallel databases.

Data Mining and Machine Learning

Data Mining and Machine Learning PDF Author: Mohammed J. Zaki
Publisher: Cambridge University Press
ISBN: 1108473989
Category : Business & Economics
Languages : en
Pages : 779

Book Description
New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

High-Utility Pattern Mining

High-Utility Pattern Mining PDF Author: Philippe Fournier-Viger
Publisher: Springer
ISBN: 3030049213
Category : Technology & Engineering
Languages : en
Pages : 343

Book Description
This book presents an overview of techniques for discovering high-utility patterns (patterns with a high importance) in data. It introduces the main types of high-utility patterns, as well as the theory and core algorithms for high-utility pattern mining, and describes recent advances, applications, open-source software, and research opportunities. It also discusses several types of discrete data, including customer transaction data and sequential data. The book consists of twelve chapters, seven of which are surveys presenting the main subfields of high-utility pattern mining, including itemset mining, sequential pattern mining, big data pattern mining, metaheuristic-based approaches, privacy-preserving pattern mining, and pattern visualization. The remaining five chapters describe key techniques and applications, such as discovering concise representations and regular patterns.

Modeling Decisions for Artificial Intelligence

Modeling Decisions for Artificial Intelligence PDF Author: Vicenç Torra
Publisher: Springer Science & Business Media
ISBN: 3540882685
Category : Business & Economics
Languages : en
Pages : 247

Book Description
This book constitutes the refereed proceedings of the 5th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2008, held in Sabadell, Spain, in October 2008. The 19 revised full papers presented together with 2 invited lectures were thoroughly reviewed and selected from 43 submissions; they are devoted to theory and tools for modeling decisions, as well as applications that encompass decision making processes and information fusion techniques. The papers are organized in topical sections on aggregation operators, decision making, clustering and similarity, computational intelligence and optimization, as well as data privacy.