Data Mining With Ontologies Implementations Findings And Frameworks
Data Mining With Ontologies Implementations Findings And Frameworks Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Data Mining With Ontologies Implementations Findings And Frameworks book. This book definitely worth reading, it is an incredibly well-written.
Data Mining with Ontologies: Implementations, Findings, and Frameworks by Nigro, Hector Oscar,Gonzalez Cisaro, Sandra Elizabeth,Xodo, Daniel Hugo Pdf
"Prior knowledge in data mining is helpful for selecting suitable data and mining techniques, pruning the space of hypothesis, representing the output in a comprehensible way, and improving the overall method. This book examines methodologies and research for the development of ontological foundations for data mining to enhance the ability of ontology utilization and design"--Provided by publisher.
Data Mining and Medical Knowledge Management: Cases and Applications by Berka, Petr,Rauch, Jan,Zighed, Djamel Abdelkader Pdf
The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.
Health Information Systems: Concepts, Methodologies, Tools, and Applications by Rodrigues, Joel J.P.C. Pdf
"This reference set provides a complete understanding of the development of applications and concepts in clinical, patient, and hospital information systems"--Provided by publisher.
Data Mining Techniques in Grid Computing Environments by Werner Dubitzky Pdf
Based around eleven international real life case studies and including contributions from leading experts in the field this groundbreaking book explores the need for the grid-enabling of data mining applications and provides a comprehensive study of the technology, techniques and management skills necessary to create them. This book provides a simultaneous design blueprint, user guide, and research agenda for current and future developments and will appeal to a broad audience; from developers and users of data mining and grid technology, to advanced undergraduate and postgraduate students interested in this field.
Model and Data Engineering by Ladjel Bellatreche,Filipe Mota Pinto Pdf
This book constitutes the refereed proceedings of the First International Conference on Model and Data Engineering, MEDI 2011, held in Óbidos, Portugal, in September 2011. The 18 revised full papers presented together with 8 short papers and three keynotes were carefully reviewed and selected from 67 submissions. The papers are organized in topical sections on ontology engineering; Web services and security; advanced systems; knowledge management; model specification and verification; and models engineering.
Inductive Databases and Constraint-Based Data Mining by Sašo Džeroski,Bart Goethals,Panče Panov Pdf
This book is about inductive databases and constraint-based data mining, emerging research topics lying at the intersection of data mining and database research. The aim of the book as to provide an overview of the state-of- the art in this novel and - citing research area. Of special interest are the recent methods for constraint-based mining of global models for prediction and clustering, the uni?cation of pattern mining approaches through constraint programming, the clari?cation of the re- tionship between mining local patterns and global models, and the proposed in- grative frameworks and approaches for inducive databases. On the application side, applications to practically relevant problems from bioinformatics are presented. Inductive databases (IDBs) represent a database view on data mining and kno- edge discovery. IDBs contain not only data, but also generalizations (patterns and models) valid in the data. In an IDB, ordinary queries can be used to access and - nipulate data, while inductive queries can be used to generate (mine), manipulate, and apply patterns and models. In the IDB framework, patterns and models become ”?rst-class citizens” and KDD becomes an extended querying process in which both the data and the patterns/models that hold in the data are queried.
Discovery Science by João Gama,Vitor Santos Costa,Alipio Jorge,Pavel Brazdil Pdf
This book constitutes the refereed proceedings of the twelfth International Conference, on Discovery Science, DS 2009, held in Porto, Portugal, in October 2009. The 35 revised full papers presented were carefully selected from 92 papers. The scope of the conference includes the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their applications.
New Fundamental Technologies in Data Mining by Kimito Funatsu Pdf
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.
Environmental Software Systems. Frameworks of eEnvironment by Jiri Hrebicek,Gerald Schimak,Ralf Denzer Pdf
This book constitutes the refereed proceedings of the 9th IFIP WG 5.11 International Symposium on Environmental Software Systems, ISESS 2011, held in Brno, Czech Republic, in June 2011. The 68 revised full papers presented together with four invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in the following topical sections: eEnvironment and cross-border services in digital agenda for Europe; environmental information systems and services - infrastructures and platforms; semantics and environment; information tools for global environmental assessment; climate services and environmental tools for urban planning and climate change - applications and services.
Mobility, Data Mining and Privacy by Fosca Giannotti,Dino Pedreschi Pdf
Mobile communications and ubiquitous computing generate large volumes of data. Mining this data can produce useful knowledge, yet individual privacy is at risk. This book investigates the various scientific and technological issues of mobility data, open problems, and roadmap. The editors manage a research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, and this book relates their findings in 13 chapters covering all related subjects.
Discovery Science by Johannes Fürnkranz,Eyke Hüllermeier,Tomoyuki Higuchi Pdf
This book constitutes the proceedings of the 16th International Conference on Discovery Science, DS 2013, held in Singapore in October 2013, and co-located with the International Conference on Algorithmic Learning Theory, ALT 2013. The 23 papers presented in this volume were carefully reviewed and selected from 52 submissions. They cover recent advances in the development and analysis of methods of automatic scientific knowledge discovery, machine learning, intelligent data analysis, and their application to knowledge discovery.
Exploiting Semantic Web Knowledge Graphs in Data Mining by P. Ristoski Pdf
Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process. This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation strategies from types and relations in knowledge graphs used in different data mining tasks such as classification, regression, and outlier detection. Part II, Semantic Web Knowledge Graphs Embeddings, proposes an approach that circumvents the shortcomings introduced with the approaches in Part I, developing an approach that is able to embed complete Semantic Web knowledge graphs in a low dimensional feature space where each entity and relation in the knowledge graph is represented as a numerical vector. Finally, Part III, Applications of Semantic Web Knowledge Graphs, describes a list of applications that exploit Semantic Web knowledge graphs like classification and regression, showing that the approaches developed in Part I and Part II can be used in applications in various domains. The book will be of interest to all those working in the field of data mining and KDD.
Encyclopedia of Data Warehousing and Mining, Second Edition by Wang, John Pdf
There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over 300 entries on theories, methodologies, functionalities, and applications.
Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications by Wang, John Pdf
In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.
Database Technologies: Concepts, Methodologies, Tools, and Applications by Erickson, John Pdf
"This reference expands the field of database technologies through four-volumes of in-depth, advanced research articles from nearly 300 of the world's leading professionals"--Provided by publisher.
