Linking And Mining Heterogeneous And Multi View Data
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| Author | : Deepak P |
| Publisher | : Springer |
| Total Pages | : 345 |
| Release | : 2018-12-13 |
| Genre | : Technology & Engineering |
| ISBN | : 3030018725 |
This book highlights research in linking and mining data from across varied data sources. The authors focus on recent advances in this burgeoning field of multi-source data fusion, with an emphasis on exploratory and unsupervised data analysis, an area of increasing significance with the pace of growth of data vastly outpacing any chance of labeling them manually. The book looks at the underlying algorithms and technologies that facilitate the area within big data analytics, it covers their applications across domains such as smarter transportation, social media, fake news detection and enterprise search among others. This book enables readers to understand a spectrum of advances in this emerging area, and it will hopefully empower them to leverage and develop methods in multi-source data fusion and analytics with applications to a variety of scenarios. Includes advances on unsupervised, semi-supervised and supervised approaches to heterogeneous data linkage and fusion; Covers use cases of analytics over multi-view and heterogeneous data from across a variety of domains such as fake news, smarter transportation and social media, among others; Provides a high-level overview of advances in this emerging field and empowers the reader to explore novel applications and methodologies that would enrich the field.
| Author | : Witold Pedrycz |
| Publisher | : Springer Nature |
| Total Pages | : 346 |
| Release | : 2022-05-20 |
| Genre | : Computers |
| ISBN | : 3030952398 |
This book provides timely studies on multi-view facets of data analytics by covering recent trends in processing and reasoning about data originating from an array of local sources. A multi-view nature of data analytics is encountered when working with a variety of real-world scenarios including clustering, consensus building in decision processes, computer vision, knowledge representation, big data, data streaming, among others. The chapters demonstrate recent pursuits in the methodology, theory, advanced algorithms, and applications of multi-view data analytics and bring new perspectives of data interpretation. The timely book will appeal to a broad readership including both researchers and practitioners interested in gaining exposure to the rapidly growing trend of multi-view data analytics and intelligent systems.
| Author | : Vincent Lemaire |
| Publisher | : Springer Nature |
| Total Pages | : 240 |
| Release | : 2020-12-15 |
| Genre | : Computers |
| ISBN | : 3030657426 |
This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Ghent, Belgium, in September 2020. The 15 full papers presented in this book were carefully reviewed and selected from 29 submissions. The selected papers are devoted to topics such as Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Early Classification of Temporal Data; Deep Learning and Learning Representations for Temporal Data; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Space-Temporal Statistical Analysis; Functional Data Analysis Methods; Temporal Data Streams; Interpretable Time-Series Analysis Methods; Dimensionality Reduction, Sparsity, Algorithmic Complexity and Big Data Challenge; and Bio-Informatics, Medical, Energy Consumption, Temporal Data.
| Author | : Paramartha Dutta |
| Publisher | : Springer Nature |
| Total Pages | : 670 |
| Release | : 2022-09-29 |
| Genre | : Technology & Engineering |
| ISBN | : 9811946760 |
This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2022) held at Institute of Engineering & Management, Kolkata, India, during February 23–25, 2022. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of Things (IoT), and information security.
| Author | : Leonard Barolli |
| Publisher | : Springer Nature |
| Total Pages | : 338 |
| Release | : 2023-10-28 |
| Genre | : Technology & Engineering |
| ISBN | : 3031469704 |
P2P, Grid, Cloud, and Internet computing technologies have been very fast established as breakthrough paradigms for solving complex problems by enabling aggregation and sharing of an increasing variety of distributed computational resources at large scale. Grid Computing originated as a paradigm for high performance computing, as an alternative to expensive supercomputers through different forms of large-scale distributed computing. P2P Computing emerged as a new paradigm after client-server and web-based computing and has shown useful to the development of social networking, Business to Business (B2B), Business to Consumer (B2C), Business to Government (B2G), Business to Employee (B2E), and so on. Cloud Computing has been defined as a “computing paradigm where the boundaries of computing are determined by economic rationale rather than technical limits”. Cloud computing has fast become the computing paradigm with applicability and adoption in all application domains and providing utility computing at large scale. Finally, Internet Computing is the basis of any large-scale distributed computing paradigms; it has very fast developed into a vast area of flourishing field with enormous impact on today’s information societies serving thus as a universal platform comprising a large variety of computing forms such as Grid, P2P, Cloud, and Mobile computing. The aim of the book is to provide latest research findings, innovative research results, methods, and development techniques from both theoretical and practical perspectives related to P2P, Grid, Cloud, and Internet Computing as well as to reveal synergies among such large-scale computing paradigms.
| Author | : Ladjel Bellatreche |
| Publisher | : Springer Nature |
| Total Pages | : 300 |
| Release | : 2021-08-16 |
| Genre | : Computers |
| ISBN | : 3030824721 |
This book constitutes the proceedings of the 25th European Conference on Advances in Databases and Information Systems, ADBIS 2021, held in Tartu, Estonia, in August 2021. The 18 full papers presented together with 3 keynotes were carefully reviewed and selected from 70 submissions. The selected papers span a wide spectrum of topics in databases and related technologies, tackling challenging problems and presenting inventive and efficient solutions. They are organized in 5 sessions: patterns and events, social media and text mining, indexes, queries and constraints, high-dimensional data and data streams, and data integration.
| Author | : Yizhou Sun |
| Publisher | : Morgan & Claypool Publishers |
| Total Pages | : 162 |
| Release | : 2012 |
| Genre | : Computers |
| ISBN | : 1608458806 |
Investigates the principles and methodologies of mining heterogeneous information networks. Departing from many existing network models that view interconnected data as homogeneous graphs or networks, the semi-structured heterogeneous information network model leverages the rich semantics of typed nodes and links in a network and uncovers surprisingly rich knowledge from the network.
| Author | : Kohei Arai |
| Publisher | : Springer Nature |
| Total Pages | : 1073 |
| Release | : 2021-04-15 |
| Genre | : Technology & Engineering |
| ISBN | : 3030731030 |
This book aims to provide an international forum for scholarly researchers, practitioners and academic communities to explore the role of information and communication technologies and its applications in technical and scholarly development. The conference attracted a total of 464 submissions, of which 152 submissions (including 4 poster papers) have been selected after a double-blind review process. Academic pioneering researchers, scientists, industrial engineers and students will find this series useful to gain insight into the current research and next-generation information science and communication technologies. This book discusses the aspects of communication, data science, ambient intelligence, networking, computing, security and Internet of things, from classical to intelligent scope. The authors hope that readers find the volume interesting and valuable; it gathers chapters addressing tate-of-the-art intelligent methods and techniques for solving real-world problems along with a vision of the future research.
| Author | : Harun Pirim |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 250 |
| Release | : 2018-08-01 |
| Genre | : Computers |
| ISBN | : 178923526X |
Clustering has emerged as one of the more fertile fields within data analytics, widely adopted by companies, research institutions, and educational entities as a tool to describe similar/different groups. The book Recent Applications in Data Clustering aims to provide an outlook of recent contributions to the vast clustering literature that offers useful insights within the context of modern applications for professionals, academics, and students. The book spans the domains of clustering in image analysis, lexical analysis of texts, replacement of missing values in data, temporal clustering in smart cities, comparison of artificial neural network variations, graph theoretical approaches, spectral clustering, multiview clustering, and model-based clustering in an R package. Applications of image, text, face recognition, speech (synthetic and simulated), and smart city datasets are presented.
| Author | : Lei Meng |
| Publisher | : Springer |
| Total Pages | : 200 |
| Release | : 2019-04-30 |
| Genre | : Computers |
| ISBN | : 3030029859 |
Social media data contains our communication and online sharing, mirroring our daily life. This book looks at how we can use and what we can discover from such big data: Basic knowledge (data & challenges) on social media analytics Clustering as a fundamental technique for unsupervised knowledge discovery and data mining A class of neural inspired algorithms, based on adaptive resonance theory (ART), tackling challenges in big social media data clustering Step-by-step practices of developing unsupervised machine learning algorithms for real-world applications in social media domain Adaptive Resonance Theory in Social Media Data Clustering stands on the fundamental breakthrough in cognitive and neural theory, i.e. adaptive resonance theory, which simulates how a brain processes information to perform memory, learning, recognition, and prediction. It presents initiatives on the mathematical demonstration of ART’s learning mechanisms in clustering, and illustrates how to extend the base ART model to handle the complexity and characteristics of social media data and perform associative analytical tasks. Both cutting-edge research and real-world practices on machine learning and social media analytics are included in the book and if you wish to learn the answers to the following questions, this book is for you: How to process big streams of multimedia data? How to analyze social networks with heterogeneous data? How to understand a user’s interests by learning from online posts and behaviors? How to create a personalized search engine by automatically indexing and searching multimodal information resources? .
