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Books > Computing & IT > Applications of computing > Databases > Data mining
This book reports on cutting-edge research carried out within the context of the EU-funded Dicode project, which aims at facilitating and augmenting collaboration and decision making in data-intensive and cognitively complex settings. Whenever appropriate, Dicode builds on prominent high-performance computing paradigms and large data processing technologies to meaningfully search, analyze, and aggregate data from diverse, extremely large and rapidly evolving sources. The Dicode approach and services are fully explained and particular emphasis is placed on deepening insights regarding the exploitation of big data, as well as on collaboration and issues relating to sense-making support. Building on current advances, the solution developed in the Dicode project brings together the reasoning capabilities of both the machine and humans. It can be viewed as an innovative "workbench" incorporating and orchestrating a set of interoperable services that reduce the data intensiveness and complexity overload at critical decision points to a manageable level, thus permitting stakeholders to be more productive and effective in their work practices.
A broad spectrum of modern Information Technology (IT) tools, techniques, main developments and still open challenges is presented. Emphasis is on new research directions in various fields of science and technology that are related to data analysis, data mining, knowledge discovery, information retrieval, clustering and classification, decision making and decision support, control, computational mathematics and physics, to name a few. Applications in many relevant fields are presented, notably in telecommunication, social networks, recommender systems, fault detection, robotics, image analysis and recognition, electronics, etc. The methods used by the authors range from high level formal mathematical tools and techniques, through algorithmic and computational tools, to modern metaheuristics.
This book shows how to look at ways of visualizing large datasets, whether large in numbers of cases, or large in numbers of variables, or large in both. All ideas are illustrated with displays from analyses of real datasets and the importance of interpreting displays effectively is emphasized. Graphics should be drawn to convey information and the book includes many insightful examples. New approaches to graphics are needed to visualize the information in large datasets and most of the innovations described in this book are developments of standard graphics. The book is accessible to readers with some experience of drawing statistical graphics.
The development of Operations Research (OR) requires constant improvements, such as the integration of research results with business applications and innovative educational practice. The full deployment and commercial exploitation of goods and services generally need the construction of strong synergies between educational institutions and businesses. The IO2015 -XVII Congress of APDIO aims at strengthening the knowledge triangle in education, research and innovation, in order to maximize the contribution of OR for sustainable growth, the promoting of a knowledge-based economy, and the smart use of finite resources. The IO2015-XVII Congress of APDIO is a privileged meeting point for the promotion and dissemination of OR and related disciplines, through the exchange of ideas among teachers, researchers, students , and professionals with different background, but all sharing a common desire that is the development of OR.
This work reviews the state of the art in SVM and perceptron classifiers. A Support Vector Machine (SVM) is easily the most popular tool for dealing with a variety of machine-learning tasks, including classification. SVMs are associated with maximizing the margin between two classes. The concerned optimization problem is a convex optimization guaranteeing a globally optimal solution. The weight vector associated with SVM is obtained by a linear combination of some of the boundary and noisy vectors. Further, when the data are not linearly separable, tuning the coefficient of the regularization term becomes crucial. Even though SVMs have popularized the kernel trick, in most of the practical applications that are high-dimensional, linear SVMs are popularly used. The text examines applications to social and information networks. The work also discusses another popular linear classifier, the perceptron, and compares its performance with that of the SVM in different application areas.>
Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.
Advance Praise for Indian Mujahideen: Computational Analysis and Public Policy "This book presents a highly innovative computational approach to analyzing the strategic behavior of terrorist groups and formulating counter-terrorism policies. It would be very useful for international security analysts and policymakers." Uzi Arad, National Security Advisor to the Prime Minister of Israel and Head, Israel National Security Council (2009-2011) "An important book on a complex security problem. Issues have been analysed in depth based on quality research. Insightful and well-balanced in describing the way forward." Naresh Chandra, Indian Ambassador to the USA (1996-2001) and Cabinet Secretary (1990-1992). "An objective and clinical account of the origins, aims, extra-territorial links and modus-operandi, of a growingly dangerous terrorist organization that challenges the federal, democratic, secular and pluralistic ethos of India's polity. The authors have meticulously researched and analysed the multi-faceted challenges that the "Indian Mujahideen" poses and realistically dwelt on the ways in which these challenges could be faced and overcome." G. Parthasarathy, High Commissioner of India to Australia (1995-1998) and Pakistan (1998-2000). This book provides the first in-depth look at how advanced mathematics and modern computing technology can influence insights on analysis and policies directed at the Indian Mujahideen (IM) terrorist group. The book also summarizes how the IM group is committed to the destabilization of India by leveraging links with other terror groups such as Lashkar-e-Taiba, and through support from the Pakistani Government and Pakistan's intelligence service. Foreword by The Hon. Louis J. Freeh.
The book presents high quality papers presented at the International Conference on Computational Intelligence in Data Mining (ICCIDM 2016) organized by School of Computer Engineering, Kalinga Institute of Industrial Technology (KIIT), Bhubaneswar, Odisha, India during December 10 - 11, 2016. The book disseminates the knowledge about innovative, active research directions in the field of data mining, machine and computational intelligence, along with current issues and applications of related topics. The volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science.
This book constitutes the thoroughly refereed short papers, workshops and Doctoral Consortium papers of the 20th East European Conference on Advances in Databases and Information Systems, ADBIS 2016, held in Prague, Czech Republic, in August 2016. The 11 short papers and one historical paper were carefully selected and reviewed from 85 submissions. The rest of papers was selected from reviewing processes of 2 workshops and Doctoral Consortium. The papers are organized in topical sections on ADBIS Short Papers, Third International Workshop on Big Data Applications and Principles (BigDap 2016), Second International Workshop on Data Centered Smart Applications (DCSA 2016) and ADBIS Doctoral Consortium.
This book constitutes the thoroughly refereed post-conference proceedings of the International Conference on Industrial IoT Technologies and Applications, IoT 2016, held in GuangZhou, China, in March 2016. The volume contains 26 papers carefully reviewed and selected from 55 submissions focusing on topics such as big data, cloud computing, Internet of Things (IoT).
The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.
This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.
This book constitutes the proceedings of the Third International Conference on Decision Support Systems, ICDSST 2017, held in Namur, Belgium, in May 2017. The EWG-DSS series of the International Conference on Decision Support System Technology (ICDSST) offers a platform for European and international DSS communities, comprising the academic and industrial sectors, in order to present state-of-the-art DSS research and developments, to discuss current challenges that surround decision-making processes, to exchange ideas about realistic and innovative solutions, and to co-develop potential business opportunities. The main topic of this year's conference was "Data, Information and Knowledge Visualization in Decision Making". The 13 papers presented in this volume were carefully reviewed and selected from 53 submissions. They were organized in topical sections named: visualization case studies; visualization perspectives; analytics and decision; and Multi-Criteria Decision Making.
In response to the need to improve road traffic operation, researchers implement advanced technologies and integration of systems and data, and develop state-of-the-art applications to assist traffic engineers. This SpringerBrief introduces three novel Web applications which can be an exceptional resource and a good visualization tool for traffic operators, managers, and analysts to monitor the congestion, and analyze incidents and signal performance measures. The applications offer more detailed analysis providing users with insights from different levels and perspectives. The benefit of providing these automated and interactive visualization tools is more efficient estimation of the local transport networks' performance, thus facilitating the decision making process in case of emergency events.
This two volume set (CCIS 623 and 634) constitutes the refereed proceedings of the Second International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, held in Harbin, China, in August 2016. The 91 revised full papers presented were carefully reviewed and selected from 338 submissions. The papers are organized in topical sections on Research Track (Part I) and Education Track, Industry Track, and Demo Track (Part II) and cover a wide range of topics related to social computing, social media, social network analysis, social modeling, social recommendation, machine learning, data mining.
This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis in Marketing; Data Analysis in Finance and Economics; Data Analysis in Medicine and the Life Sciences; Data Analysis in the Social, Behavioural, and Health Care Sciences; Data Analysis in Interdisciplinary Domains; Classification and Subject Indexing in Library and Information Science. The book presents selected papers from the Second European Conference on Data Analysis, held at Jacobs University Bremen in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process.
This proceedings book presents recent research work and results in the area of communication and information technologies. The chapters of this book contain the main, well-selected and reviewed contributions of scientists who met at the 12th International Conference on Computing and Information Technology (IC2IT) held during 7th - 8th July 2016 in Khon Kaen, Thailand The book is divided into three parts: "User Centric Data Mining and Text Processing", "Data Mining Algoritms and their Applications" and "Optimization of Complex Networks".
This book constitutes the thoroughly refereed proceedings of the 9th Russian Summer School on Information Retrieval, RuSSIR 2015, held in Saint Petersburg, Russia, in August 2015. The volume includes 5 tutorial papers, summarizing lectures given at the event, and 6 revised papers from the school participants. The papers focus on various aspects of information retrieval.
Learn how to develop powerful data analytics applications quickly for SQL Server database administrators and developers. Organizations will be able to sift data and derive the business intelligence needed to drive business decisions and profit. The addition of R to SQL Server 2016 places a powerful analytical processor into an environment most developers are already comfortable with - Visual Studio. This book walks even the newest of users through the creation process of a powerful R-language tool set for use in analyzing and reporting on your data. As a SQL Server database administrator or developer, it is sometimes difficult to stay on the bleeding edge of technology. Microsoft's addition of R to SQL Server 2016 is sure to be a game-changer, and the language will certainly become an integral part of future releases. R is in fact widely used today in statistical and related applications, and its use is only growing. Beginning SQL Server R Services helps you jump on board this important trend by providing good examples with detailed explanations of the WHY and not just the HOW. Walks you through setup and installation of SQL Server R Services. Explains the basics of working with R Tools for Visual Studio. Provides a road map to successfully creating custom R code. What You Will Learn Discover R's role in the SQL Server 2016 hierarchy. Manage the components needed to run SQL Server R Services code. Run R-language analytics and queries inside the database. Create analytic solutions that run across multiple datasets. Gain in-depth knowledge of the R language itself. Implement custom SQL Server R Services solutions. Who This Book Is For Any level of database administrator or developer, but specifically it's for those developers with the need to develop powerful data analytics applications quickly. Seasoned R developers will appreciate the book for its robust learning pattern, using visual aids in combination with properties explanations and scenarios. Beginning SQL Server R Services is the perfect "new hire" gift for new database developers in any organization.
This book covers the major fundamentals of and the latest research on next-generation spatio-temporal recommendation systems in social media. It begins by describing the emerging characteristics of social media in the era of mobile internet, and explores the limitations to be found in current recommender techniques. The book subsequently presents a series of latent-class user models to simulate users' behaviors in decision-making processes, which effectively overcome the challenges arising from temporal dynamics of users' behaviors, user interest drift over geographical regions, data sparsity and cold start. Based on these well designed user models, the book develops effective multi-dimensional index structures such as Metric-Tree, and proposes efficient top-k retrieval algorithms to accelerate the process of online recommendation and support real-time recommendation. In addition, it offers methodologies and techniques for evaluating both the effectiveness and efficiency of spatio-temporal recommendation systems in social media. The book will appeal to a broad readership, from researchers and developers to undergraduate and graduate students.
This book constitutes the refereed proceedings of the Second International Conference on Decision Support Systems Technology, ICDSST 2016, held in Plymouth, UK, May 23-25. The theme of the event was "Decision Support Systems Addressing Sustainability & Societal Challenges", organized by the EURO (Association of European Operational Research Societies) working group of Decision Support Systems (EWG-DSS). The 15 full papers presented in this book were selected out of 51 submissions after being carefully reviewed by internationally experts from the ICDSST 2016 Program Committee and external invited reviewers. The selected papers are representative of current and relevant research activities in various areas of decision support systems, such as sustainability and societal challenges; risk management and project portfolio management; business intelligence and knowledge management; and technologies to improve system usability.
This book contains the refereed proceedings of the 19th International Conference on Business Information Systems, BIS 2016, held in Leipzig, Germany, in July 2016. The BIS conference series follows trends in academia and business research; thus the theme of the BIS 2016 conference was Smart Business Ecosystems". This recognizes that no business is an island and competition is increasingly taking place between business networks and no longer between individual companies. A variety of aspects is relevant for designing and understanding smart business ecosystems. They reach from new business models, value chains and processes to all aspects of analytical, social and enterprise applications and platforms as well as cyber-physical infrastructures. The 33 full and 1 short papers were carefully reviewed and selected from 87 submissions. They are grouped into sections on ecosystems; big and smart data; smart infrastructures; process management; business and enterprise modeling; service science; social media; and applications.
This book constitutes the refereed proceedings of the 12th International Baltic Conference on Databases and Information Systems, DB&IS 2016, held in Riga, Latvia, in July 2016. The 25 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on ontology, conceptual modeling and databases; tools, technologies and languages for model-driven development; decision support systems and data mining; advanced systems and technologies; business process modeling and performance measurement; software testing and quality assurance; linguistic components of IS; information technology in teaching and learning.
This book contains the refereed proceedings of the 17th International Conference on Business Process Modeling, Development and Support, BPMDS 2016, and the 21st International Conference on Exploring Modeling Methods for Systems Analysis and Design, EMMSAD 2016, held together with the 28th International Conference on Advanced Information Systems Engineering (CAiSE 2016) in Ljubljana, Slovenia, in June 2016. The focus theme for BPMDS 2016 papers was "Business Processes in a Connected World", for which three subthemes were identified: business processes for connecting people, connecting intelligent objects to business processes and connecting information/data/knowledge to business processes. The 17 full and 1 short paper accepted for BPMDS were selected from 48 submissions and are grouped into topical sections on process execution support; improving usability of process models; social and human perspectives; new directions in process modeling; consistency, correctness and compliance; process and data mining; and process variability. The intention of EMMSAD is to solicit papers related to the field of information systems analysis and design including numerous information modeling methods and notations that are typically evolving. These ongoing changes significantly impact the way information systems, enterprises, and business processes are being analyzed and designed in practice. The 12 full papers accepted for EMMSAD were chosen from 19 submissions and are grouped into topical sections on fundamental issues in modeling; requirements and regulations; enterprise and software ecosystem modeling; information and process model quality; meta-modeling and domain specific modeling and model composition; and modeling of architecture and design.
This book constitutes the refereed proceedings of the 12th EUROLAN Summer School on Linguistic Linked Open Data and its Satellite Workshop on Social Media and the Web of Linked Data, RUMOUR 2015, held in Sibiu, Romania, in July 2015. The 10 revised full papers presented together with 12 abstracts of tutorials were carefully reviewed and selected from 21 submissions. |
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