Continuous Spatial Query Processing Over Clustered Data Set
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| Author | : Leonard Barolli |
| Publisher | : Springer Nature |
| Total Pages | : 801 |
| Release | : 2021-04-23 |
| Genre | : Computers |
| ISBN | : 3030751007 |
This book covers the theory, design and applications of computer networks, distributed computing and information systems. Networks of today are going through a rapid evolution, and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low-power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence and actuations is emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low-cost and high-volume applications. Several of such applications have been difficult to realize because of many interconnections problems. To fulfill their large range of applications, different kinds of networks need to collaborate, and wired and next-generation wireless systems should be integrated in order to develop high-performance computing solutions to problems arising from the complexities of these networks. The aim of the book “Advanced Information Networking and Applications” is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications.
| Author | : Guojun Gan |
| Publisher | : SIAM |
| Total Pages | : 430 |
| Release | : 2020-11-10 |
| Genre | : Mathematics |
| ISBN | : 1611976332 |
Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
| Author | : Dimitris Papadias |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 487 |
| Release | : 2007-06-29 |
| Genre | : Business & Economics |
| ISBN | : 3540735399 |
The refereed proceedings of the 10th International Symposium on Spatial and Temporal Databases, SSTD 2007, held in Boston, MA, USA in July 2007. The 26 revised full papers were thoroughly reviewed and selected from a total of 76 submissions. The papers are classified in the following categories, each corresponding to a conference session: continuous monitoring, indexing and query processing, mining, aggregation and interpolation, semantics and modeling, privacy, uncertainty and approximation, streaming data, distributed systems, and spatial networks.
| Author | : John F. Roddick |
| Publisher | : Springer |
| Total Pages | : 184 |
| Release | : 2003-06-29 |
| Genre | : Computers |
| ISBN | : 3540452443 |
This volume contains updated versions of the ten papers presented at the First International Workshop on Temporal, Spatial and Spatio-Temporal Data Mining (TSDM 2000) held in conjunction with the 4th European Conference on Prin- ples and Practice of Knowledge Discovery in Databases (PKDD 2000) in Lyons, France in September, 2000. The aim of the workshop was to bring together experts in the analysis of temporal and spatial data mining and knowledge discovery in temporal, spatial or spatio-temporal database systems as well as knowledge engineers and domain experts from allied disciplines. The workshop focused on research and practice of knowledge discovery from datasets containing explicit or implicit temporal, spatial or spatio-temporal information. The ten original papers in this volume represent those accepted by peer review following an international call for papers. All papers submitted were refereed by an international team of data mining researchers listed below. We would like to thank the team for their expert and useful help with this process. Following the workshop, authors were invited to amend their papers to enable the feedback received from the conference to be included in the ?nal papers appearing in this volume. A workshop report was compiled by Kathleen Hornsby which also discusses the panel session that was held.
| Author | : Garcia Marquez, Fausto Pedro |
| Publisher | : IGI Global |
| Total Pages | : 499 |
| Release | : 2019-10-04 |
| Genre | : Computers |
| ISBN | : 1799801071 |
As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is necessary. The Handbook of Research on Big Data Clustering and Machine Learning is an essential reference source that synthesizes the analytic principles of clustering and machine learning to big data and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management. Featuring research on topics such as project management, contextual data modeling, and business information systems, this book is ideally designed for engineers, economists, finance officers, marketers, decision makers, business professionals, industry practitioners, academicians, students, and researchers seeking coverage on the implementation of big data and machine learning within specific professional fields.
| Author | : Ahmed R. Mahmood |
| Publisher | : Springer Nature |
| Total Pages | : 98 |
| Release | : 2022-05-31 |
| Genre | : Computers |
| ISBN | : 3031018672 |
Text data that is associated with location data has become ubiquitous. A tweet is an example of this type of data, where the text in a tweet is associated with the location where the tweet has been issued. We use the term spatial-keyword data to refer to this type of data. Spatial-keyword data is being generated at massive scale. Almost all online transactions have an associated spatial trace. The spatial trace is derived from GPS coordinates, IP addresses, or cell-phone-tower locations. Hundreds of millions or even billions of spatial-keyword objects are being generated daily. Spatial-keyword data has numerous applications that require efficient processing and management of massive amounts of spatial-keyword data. This book starts by overviewing some important applications of spatial-keyword data, and demonstrates the scale at which spatial-keyword data is being generated. Then, it formalizes and classifies the various types of queries that execute over spatial-keyword data. Next, it discusses important and desirable properties of spatial-keyword query languages that are needed to express queries over spatial-keyword data. As will be illustrated, existing spatial-keyword query languages vary in the types of spatial-keyword queries that they can support. There are many systems that process spatial-keyword queries. Systems differ from each other in various aspects, e.g., whether the system is batch-oriented or stream-based, and whether the system is centralized or distributed. Moreover, spatial-keyword systems vary in the types of queries that they support. Finally, systems vary in the types of indexing techniques that they adopt. This book provides an overview of the main spatial-keyword data-management systems (SKDMSs), and classifies them according to their features. Moreover, the book describes the main approaches adopted when indexing spatial-keyword data in the centralized and distributed settings. Several case studies of {SKDMSs} are presented along with the applications and query types that these {SKDMSs} are targeted for and the indexing techniques they utilize for processing their queries. Optimizing the performance and the query processing of {SKDMSs} still has many research challenges and open problems. The book concludes with a discussion about several important and open research-problems in the domain of scalable spatial-keyword processing.
| Author | : Yannis Manolopoulos |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 297 |
| Release | : 2012-09-07 |
| Genre | : Computers |
| ISBN | : 1441985905 |
Advanced Database Indexing begins by introducing basic material on storage media, including magnetic disks, RAID systems and tertiary storage such as optical disk and tapes. Typical access methods (e.g. B+ trees, dynamic hash files and secondary key retrieval) are also introduced. The remainder of the book discusses recent advances in indexing and access methods for particular database applications. More specifically, issues such as external sorting, file structures for intervals, temporal access methods, spatial and spatio-temporal indexing, image and multimedia indexing, perfect external hashing methods, parallel access methods, concurrency issues in indexing and parallel external sorting are presented for the first time in a single book. Advanced Database Indexing is an excellent reference for database professionals and may be used as a text for advanced courses on the topic.
| Author | : Alberto Belussi |
| Publisher | : MDPI |
| Total Pages | : 170 |
| Release | : 2021-01-20 |
| Genre | : Technology & Engineering |
| ISBN | : 3039367501 |
This book aims at promoting new and innovative studies, proposing new architectures or innovative evolutions of existing ones, and illustrating experiments on current technologies in order to improve the efficiency and effectiveness of distributed and cluster systems when they deal with spatiotemporal data.
| Author | : Yan, Li |
| Publisher | : IGI Global |
| Total Pages | : 652 |
| Release | : 2015-09-25 |
| Genre | : Computers |
| ISBN | : 1466687681 |
Research and development surrounding the use of data queries is receiving increased attention from computer scientists and data specialists alike. Through the use of query technology, large volumes of data in databases can be retrieved, and information systems built based on databases can support problem solving and decision making across industries. The Handbook of Research on Innovative Database Query Processing Techniques focuses on the growing topic of database query processing methods, technologies, and applications. Aimed at providing an all-inclusive reference source of technologies and practices in advanced database query systems, this book investigates various techniques, including database and XML queries, spatiotemporal data queries, big data queries, metadata queries, and applications of database query systems. This comprehensive handbook is a necessary resource for students, IT professionals, data analysts, and academicians interested in uncovering the latest methods for using queries as a means to extract information from databases. This all-inclusive handbook includes the latest research on topics pertaining to information retrieval, data extraction, data management, design and development of database queries, and database and XM queries.
| Author | : Christian S. Jensen |
| Publisher | : Springer Nature |
| Total Pages | : 801 |
| Release | : 2021-04-06 |
| Genre | : Computers |
| ISBN | : 3030731979 |
The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.
