Proceedings of the 19th International Conference on World Wide Web PDF Download

Author: Paul Jones
Publisher:
ISBN: 9781605587998
Category : Internet
Languages : en
Pages : 1365

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Book Description
WWW '10: The 19th International World Wide Web Conference Apr 26, 2010-Apr 30, 2010 Raleigh, USA. You can view more information about this proceeding and all of ACMs other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

Author: Shuguang Cui
Publisher: Cambridge University Press
ISBN: 1107099005
Category : Computers
Languages : en
Pages : 459

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Book Description
Examines the crucial interaction between big data and communication, social and biological networks using critical mathematical tools and state-of-the-art research.

Author: Xiang Zhao
Publisher: Springer Nature
ISBN: 3031203097
Category : Computers
Languages : en
Pages : 749

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Book Description
This book constitutes the proceedings of the 19th International Conference on Web Information Systems and Applications, WISA 2022, held in Dalian, China, in September 2022. The 45 full papers and 19 short papers presented were carefully reviewed and selected from 212 submissions. The papers are grouped in topical sections on knowledge graph, natural language processing, world wide web, machine learning, query processing and algorithm, recommendation, data privacy and security, and blockchain.

Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1466665440
Category : Business & Economics
Languages : en
Pages : 1655

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Book Description
Over generations, human society has woven a rich tapestry of culture, art, architecture, and history, personified in artifacts, monuments, and landmarks arrayed across the globe. Individual communities are looking to exploit these local treasures for the benefit of the travelers who come to see them. Hospitality, Travel, and Tourism: Concepts, Methodologies, Tools, and Applications considers the effect of cultural heritage and destinations of interest on the global economy from the viewpoints of both visitor and host. This broadly-focused, multi-volume reference will provide unique insights for travelers, business leaders, sightseers, cultural preservationists, and others interested in the unique variety of human ingenuity and innovation around the world.

Author: Witold Pedrycz
Publisher: Springer
ISBN: 3319303198
Category : Technology & Engineering
Languages : en
Pages : 457

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Book Description
This edited volume provides the reader with a fully updated, in-depth treatise on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of models of sentiment analysis and ontology –oriented engineering. The volume involves studies devoted to key issues of sentiment analysis, sentiment models, and ontology engineering. The book is structured into three main parts. The first part offers a comprehensive and prudently structured exposure to the fundamentals of sentiment analysis and natural language processing. The second part consists of studies devoted to the concepts, methodologies, and algorithmic developments elaborating on fuzzy linguistic aggregation to emotion analysis, carrying out interpretability of computational sentiment models, emotion classification, sentiment-oriented information retrieval, a methodology of adaptive dynamics in knowledge acquisition. The third part includes a plethora of applications showing how sentiment analysis and ontologies becomes successfully applied to investment strategies, customer experience management, disaster relief, monitoring in social media, customer review rating prediction, and ontology learning. This book is aimed at a broad audience of researchers and practitioners. Readers involved in intelligent systems, data analysis, Internet engineering, Computational Intelligence, and knowledge-based systems will benefit from the exposure to the subject matter. The book may also serve as a highly useful reference material for graduate students and senior undergraduate students.

Author: Brooke Foucault Welles
Publisher: Oxford University Press, USA
ISBN: 0190460512
Category : Language Arts & Disciplines
Languages : en
Pages : 676

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Book Description
Communication technologies, including the internet, social media, and countless online applications create the infrastructure and interface through which many of our interactions take place today. This form of networked communication creates new questions about how we establish relationships, engage in public, build a sense of identity, and delimit the private domain. The ubiquitous adoption of new technologies has also produced, as a byproduct, new ways of observing the world: many of our interactions now leave a digital trail that, if followed, can help us unravel the rhythms of social life and the complexity of the world we inhabit--and thus help us reconstruct the logic of social order and change. The analysis of digital data requires partnerships across disciplinary boundaries that--although on the rise--are still uncommon. Social scientists and computer scientists have never been closer in their goals of trying to understand communication dynamics, but there are not many venues where they can engage in an open exchange of methods and theoretical insights. This handbook brings together scholars across the social and technological sciences to lay the foundations of communication research in the networked age, and to provide a canon of how research should be conducted in the digital era. The contributors highlight the main theories currently guiding their research in digital communication, and discuss state-of-the-art methodological tools, including automated text analysis, the analysis of networks, and the use of natural experiments in virtual environments. Following a general introduction, the handbook covers network and information flow, communication and organizational dynamics, interactions and social capital, mobility and space, political communication and behavior, and the ethics of digital research.

Author: Charu C. Aggarwal
Publisher: Springer Science & Business Media
ISBN: 1461432235
Category : Computers
Languages : en
Pages : 527

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Book Description
Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

Author: Yelena Mejova
Publisher: Cambridge University Press
ISBN: 1316300927
Category : Computers
Languages : en
Pages : 185

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Book Description
How can Twitter data be used to study individual-level human behavior and social interaction on a global scale? This book introduces readers to the methods, opportunities, and challenges of using Twitter data to analyze phenomena ranging from the number of people infected by the flu, to national elections, to tomorrow's stock prices. Each chapter, written by leading domain experts in clear and accessible language, takes the reader to the forefront of the newly emerging field of computational social science. An introductory chapter on Twitter data analysis provides an overview of key tools and skills, and gives pointers on how to get started, while the case studies demonstrate shortcomings, limitations, and pitfalls of Twitter data as well as its advantages. The book will be an excellent resource for social science students and researchers wanting to explore the use of online data.

Author: Marenglen Biba
Publisher: Springer Science & Business Media
ISBN: 3642229123
Category : Computers
Languages : en
Pages : 449

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Book Description
The rapidly growing volume of available digital documents of various formats and the possibility to access these through Internet-based technologies, have led to the necessity to develop solid methods to properly organize and structure documents in large digital libraries and repositories. Due to the extremely large volumes of documents and to their unstructured form, most of the research efforts in this direction are dedicated to automatically infer structure and schemas that can help to better organize huge collections of documents and data. This book covers the latest advances in structure inference in heterogeneous collections of documents and data. The book brings a comprehensive view of the state-of-the-art in the area, presents some lessons learned and identifies new research issues, challenges and opportunities for further research agenda and developments. The selected chapters cover a broad range of research issues, from theoretical approaches to case studies and best practices in the field. Researcher, software developers, practitioners and students interested in the field of learning structure and schemas from documents will find the comprehensive coverage of this book useful for their research, academic, development and practice activity.

Author: Edward Curry
Publisher: Springer Nature
ISBN: 3030296652
Category : Computers
Languages : en
Pages : 325

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Book Description
This open access book explores the dataspace paradigm as a best-effort approach to data management within data ecosystems. It establishes the theoretical foundations and principles of real-time linked dataspaces as a data platform for intelligent systems. The book introduces a set of specialized best-effort techniques and models to enable loose administrative proximity and semantic integration for managing and processing events and streams. The book is divided into five major parts: Part I “Fundamentals and Concepts” details the motivation behind and core concepts of real-time linked dataspaces, and establishes the need to evolve data management techniques in order to meet the challenges of enabling data ecosystems for intelligent systems within smart environments. Further, it explains the fundamental concepts of dataspaces and the need for specialization in the processing of dynamic real-time data. Part II “Data Support Services” explores the design and evaluation of critical services, including catalog, entity management, query and search, data service discovery, and human-in-the-loop. In turn, Part III “Stream and Event Processing Services” addresses the design and evaluation of the specialized techniques created for real-time support services including complex event processing, event service composition, stream dissemination, stream matching, and approximate semantic matching. Part IV “Intelligent Systems and Applications” explores the use of real-time linked dataspaces within real-world smart environments. In closing, Part V “Future Directions” outlines future research challenges for dataspaces, data ecosystems, and intelligent systems. Readers will gain a detailed understanding of how the dataspace paradigm is now being used to enable data ecosystems for intelligent systems within smart environments. The book covers the fundamental theory, the creation of new techniques needed for support services, and lessons learned from real-world intelligent systems and applications focused on sustainability. Accordingly, it will benefit not only researchers and graduate students in the fields of data management, big data, and IoT, but also professionals who need to create advanced data management platforms for intelligent systems, smart environments, and data ecosystems.