الصفحة 10
الصفحة 10
Data mining and Knowledge discovery handbook
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 Approaches Based on Rule Induction Techniques
This book will give the reader a perspective into the core theory and practice of data mining and knowledge discovery (DM&KD). Its chapters combine many theoretical foundations for various DM&KD methods, and they present a rich array of examples—many of which are drawn from real-life applications. Most of the theoretical developments discussed are accompanied by an extensive empirical analysis, which should give the reader both a deep theoretical and practical insight into the subjects covered.
Data Mining and Diagnosing IC Fails
This book brings together a large number of analysis techniques that are suitable for IC fail data, but that are not available elsewhere in a single place. Several of the techniques, in fact, have been presented only recently in technical conferences. The purpose of the book is to bring together in one place a large number of analysis, data mining and diagnosis techniques that have proven to be useful in analyzing IC fails. The descriptions of the techniques and analysis routines is sufficiently detailed that profession manufacturing engineers can implement them in their own work environment
Data Mining and Bioinformatics ; 1st International Workshop, VDMB 2006, Seoul, Korea, September 11, 2006, Revised Selected Papers
This volume contains the papers presented at the inaugural workshop on Data Mining and Bioinformatics at the 32nd International Conference on Very Large Data Bases (VLDB). The purpose of this workshop was to begin bringing - gether researchersfrom database, data mining, and bioinformatics areas to help leverage respective successes in each to the others.
Data Mining : Theory, Methodology, Techniques, and Applications
This volume provides a snapshot of the current state of the art in data mining, presenting it both in terms of technical developments and industrial applications. The collection of chapters is based on works presented at the Australasian Data Mining conferences and industrial forums.
Data mining : Concepts, models, methods, and algorithms ; 3rd ed.
Presents the latest techniques for analyzing and extracting information from large amounts of data in high-dimensional data spaces. Explores big data and cloud computing Examines deep learning Includes information on convolutional neural networks (CNN) Offers reinforcement learning Contains semi-supervised learning and S3VM Reviews model evaluation for unbalanced data
Data Mining : A Knowledge Discovery Approach
This book on data mining details the unique steps of the knowledge discovery process that prescribe the sequence in which data mining projects should be performed. Data Mining offers an authoritative treatment of all development phases from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes this book from other texts in the area. It concentrates on data preparation, clustering and association rule learning (required for processing unsupervised data), decision trees, rule induction algorithms, neural networks, and many other data mining methods, focusing predominantly on those which have proven successful in data mining projects.
Data Management. Data, Data Everywhere ; 24th British National Conference on Databases, BNCOD 24, Glasgow, UK, July 3-5, 2007, Proceedings
One of the most pressing challenges is to ?nd ways of evolving database technology to cope with its new role in underpinning the massively distributed and heterogeneous applications built on top of the Internet. This has afiected both the ways in which data has been accessed and the ways in which it is represented, with XML data management becoming an important issue and, as such, heavily represented at this conference. It has also brought back issues of performance that might have been considered largely solved by the improvements in hardware, since data now has to be managed on devices of low power and small memory as well as on standard client and powerful server machines. We therefore invited papers on all aspects of data management, particularly related to how dataisused in the ubiquitous environment of the modern Internet by complex distributed and scientific applications.
Data Management Technologies and Applications ; 8th International Conference, DATA 2019, Prague, Czech Republic, July 26–28, 2019, Revised Selected Papers
This book constitutes the thoroughly refereed proceedings of the 8th International Conference on Data Management Technologies and Applications, DATA 2019, held in Prague, Czech Republic, in July 2019. The 8 revised full papers were carefully reviewed and selected from 90 submissions. The papers deal with the following topics: decision support systems, data analytics, data and information quality, digital rights management, big data, knowledge management, ontology engineering, digital libraries, mobile databases, object-oriented database systems, and data integrity.
Data Integration in the Life Sciences ; Vol. 4075 ; 3rd International Workshop, DILS 2006, Hinxton, UK, July 20-22, 2006, Proceedings
Data management and data integration are fundamental problems in the life sciences. Advances in molecular biology and molecular medicine are almost u- versallyunderpinned by enormouse?orts in data management,data integration, automatic data quality assurance, and computational data analysis. Many hot topics in the life sciences, such as systems biology, personalized medicine, and pharmacogenomics, critically depend on integrating data sets and applications producedby di?erent experimentalmethods, in di?erent researchgroups,andat di?erent levels of granularity.
Data integration in the life sciences ; Vol. 3615 ; 2nd international workshop, DILS 2005, San Diego, CA, USA, July 20-22, 2005, Proceedings
Constitutes the refereed proceedings of the Second International Workshop on Data Integration in the Life Sciences, DILS 2005, held in San Diego, CA, USA in July 2005. The papers are organized in sections on user applications, ontologies, data integration, and others, and address the issues in data integration from the life science point of view.
Data Integration in the Life Sciences ; 5th International Workshop, DILS 2008, Evry, France, June 25-27, 2008. Proceedings
This book constitutes the refereed proceedings of the 5th International Workshop on Data Integration in the Life Sciences, DILS 2008, held in Evry, France in June 2008.
Data and applications security and privacy XXXIV ; 34th Annual IFIP WG 11.3 Conference, DBSec 2020, Regensburg, Germany, June 25–26, 2020, Proceedings
This book constitutes the refereed proceedings of the 34th Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy, DBSec 2020, held in Regensburg, Germany, in June 2020.* The 14 full papers and 8 short papers presented were carefully reviewed and selected from 39 submissions. The papers present high-quality original research from academia, industry, and government on theoretical and practical aspects of information security. They are organized in topical sections named network and cyber-physical systems security; information flow and access control; privacy-preserving computation; visualization and analytics for security; spatial systems and crowdsourcing security; and secure outsourcing and privacy.
Data analytics, computational statistics, and operations research for engineers : Methodologies and applications
Presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information.
Data Analysis, Machine Learning and Applications ; Proceedings of the 31st Annual Conference of the Gesellschaft für Klassifikation e.V., Albert-Ludwigs-Universität Freiburg, March 7–9, 2007
This volume contains the revised versions of selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft für Klassifikation - GfKl).
Data Algorithms with Spark
Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. you will: Learn how to select Spark transformations for optimized solutions Explore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions() Understand data partitioning for optimized queries Build and apply a model using PySpark design patterns Apply motif-finding algorithms to graph data Analyze graph data by using the GraphFrames API Apply PySpark algorithms to clinical and genomics data Learn how to use and apply feature engineering in ML algorithms Understand and use practical and pragmatic data design patterns
Cyber-physical systems : Foundations and techniques
Covers the various aspects associated with Cyber-Physical Systems (CPS) such as algorithms, application areas, and the improvement of existing technology such as machine learning, big data and robotics. The scope of CPS is tremendous. In CPS, one sees the applications of various emerging technologies such as artificial intelligence (AI), Internet of Things (IoT), machine learning (ML), deep learning (DL), big data (BD), robotics, quantum technology, etc. In almost all sectors, whether it is education, health, human resource development, skill improvement, startup strategy, etc., one sees an enhancement in the quality of output because of the emergence of CPS into the field.
Cyber Security ; 18th China Annual Conference, CNCERT 2021, Beijing, China, July 20–21, 2021, revised selected papers
This book constitutes the refereed proceedings of the 17th International Annual Conference on Cyber Security, CNCERT 2021, held in Beijing, China, in AJuly 2021. The 14 papers presented were carefully reviewed and selected from 51 submissions. The papers are organized according to the following topical sections: data security; privacy protection; anomaly detection; traffic analysis; social network security; vulnerability detection; text classification.
Current trends in database technology - EDBT 2006 ; EDBT 2006 Workshop PhD, DataX, IIDB, IIHA, ICSNW, QLQP, PIM, PaRMa, and Reactivity on the Web, Munich, Germany, March 26-31, 2006, Revised Selected Papers
This book constitutes the thoroughly refereed joint post-proceedings of nine workshops held as part of the 10th International Conference on Extending Database Technology, EDBT 2006, held in Munich, Germany in March 2006. The 70 revised full papers presented were selected from numerous submissions during two rounds of reviewing and revision.
Creating New Learning Experiences on a Global Scale ; 2nd European Conference on Technology Enhanced Learning, EC-TEL 2007, Crete, Greece, September 17-20, 2007, Proceedings
It is holding more than 500 pages of combined wisdom on Technology Enhanced Learning (TEL) in your hands! With the advance of metadata, standards, learning objects, Web 2. 0 approaches to rip, mix and burn learning, wikis, blogs, syndication, user-generated content, W- based video, games and the ubiquitous availability of computing devices we can and have to offer more flexible learning services on a global scale.It provided a unique forum for all research related to technology enhanced learning, including its interactions with knowledge management, business processes and work environments.
