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Visualization for Information Retrieval: The Information Retrieval Series, cartea 23

Autor Jin Zhang
en Limba Engleză Hardback – 16 noi 2007
The amount of digitized information available on the Internet, in digital libraries, and other forms of information systems grows at an exponential rate, while becoming more complex and more dynamic. As a consequence, information organization, information retrieval and the presentation of retrieval results have become more and more difficult.
Information visualization offers a unique method to reveal hidden patterns and contextual information in a visual presentation and allows users to seek information in an intuitive way. Jin Zhang provides a systematic explanation of the latest advancements in information retrieval visualization from both theoretical and practical perspectives. He reviews the main approaches and techniques available in the field, explains theoretical relationships between information retrieval and information visualization, and presents major information retrieval visualization algorithms and models. He then takes a detailed look at the theory and applications of information retrieval visualization for Internet traffic analysis, and Internet information searching and browsing. The author also addresses challenges such as ambiguity, metaphorical applications, and system evaluation in information retrieval visualization environments. Finally, he compares these information retrieval visualization models from the perspectives of visual spaces, semantic frameworks, projection algorithms, ambiguity, and information retrieval, and discusses important issues of information retrieval visualization and research directions for future exploration.
Readers of this book will gain an in-depth understanding of the current state of information retrieval visualization. They will be introduced to existing problems for researchers and professionals, along with technical and theoretical findings and advances made by leading researchers. The book also provides practical details for the implementation of an information retrieval visualization system.
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Specificații

ISBN-13: 9783540751472
ISBN-10: 3540751475
Pagini: 312
Ilustrații: XVIII, 294 p. 72 illus., 1 illus. in color.
Dimensiuni: 160 x 241 x 24 mm
Greutate: 0.64 kg
Ediția:2008
Editura: Springer
Colecția The Information Retrieval Series
Seria The Information Retrieval Series

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

Information Retrieval and Visualization.- Information Retrieval Preliminaries.- Visualization Models for Multiple Reference Points.- Euclidean Spatial Characteristic Based Visualization Models.- Kohonen Self-Organizing Map–An Artificial Neural Network.- Pathfinder Associative Network.- Multidimensional Scaling.- Internet Information Visualization.- Ambiguity in Information Visualization.- The Implication of Metaphors in Information Visualization.- Benchmarks and Evaluation Criteria for Information Retrieval Visualization.- Afterthoughts.

Recenzii

From the reviews:
"This book is another in the Springer information retrieval series, aimed at the academic market. … Zhang provides a guide across the field of visualisation that is comprehensive, extensive and knowledgeable to a target audience of researchers and specialists in the field. … I found Zhang’s book well structured, comprehensive, clear and interesting. … I enjoyed this book and would recommend it. It is a useful summary of the field, and is broad and comprehensive." (Andrew Neill, Informer, Issue 28, Autumn, 2008)
 
"The book offers a comprehensive and systematic review of all the methodologies and procedures developed in the area of information retrieval visualization ... [It] should be very useful to anyone who wishes to get a comprehensive account of the advances in the area of information retrieval visualization." (from the ACM Reviews by Lefteris Angelis, Aristotle University Thessaloniki, Greece)

Textul de pe ultima copertă

The amount of digitized information available on the Internet, in digital libraries, and other forms of information systems grows at an exponential rate, while becoming more complex and more dynamic. As a consequence, information organization, information retrieval and the presentation of retrieval results have become more and more difficult.
Information visualization offers a unique method to reveal hidden patterns and contextual information in a visual presentation and allows users to seek information in an intuitive way. Jin Zhang provides a systematic explanation of the latest advancements in information retrieval visualization from both theoretical and practical perspectives. He reviews the main approaches and techniques available in the field, explains theoretical relationships between information retrieval and information visualization, and presents major information retrieval visualization algorithms and models. He then takes a detailed look at the theory and applications of information retrieval visualization for Internet traffic analysis, and Internet information searching and browsing. The author also addresses challenges such as ambiguity, metaphorical applications, and system evaluation in information retrieval visualization environments. Finally, he compares these information retrieval visualization models from the perspectives of visual spaces, semantic frameworks, projection algorithms, ambiguity, and information retrieval, and discusses important issues of information retrieval visualization and research directions for future exploration.
Readers of this book will gain an in-depth understanding of the current state of information retrieval visualization. They will be introduced to existing problems for researchers and professionals, along with technical and theoretical findings and advances made by leading researchers. The book also provides practical details for the implementation of an information retrieval visualization system.

Caracteristici

First book to deal with information visualization from an information retrieval perspective Presents most important information retrieval visualization algorithms and models Details applications of information retrieval visualization for Internet traffic analysis, and internet information searching and browsing Includes supplementary material: sn.pub/extras

Notă biografică

Fei XUE is a Researcher at the School of Architecture and Urban Planning, Shenzhen University. She holds a PhD from the University of Hong Kong and previously served as a Research Fellow at the National University of Singapore. A credentialed LEED AP and BEAM Pro, Dr. Xue specialises in sustainable development, resilient cities, and healthy built environments. Her work has been recognised with the Science and Technology Progress Award from the Chinese Society of Landscape Architecture and the title of "Outstanding Engineer" in Shenzhen. She has contributed to over 40 projects and authored numerous monographs, patents, and articles in leading peer-reviewed journals. Yue FAN is a Distinguished Professor and Dean of the School of Architecture and Urban Planning at Shenzhen University. He holds a Doctor of Engineering from the University of Tokyo and is a Foreign Fellow of the Engineering Academy of Japan (EAJ). A Chartered Architect with the RIBA, Professor Fan also serves as Deputy Director of the State Key Laboratory of Subtropical Architecture and Urban Science. He is a recipient of the National Teaching Achievement Award (First Prize) and the Huaxia Construction Science and Technology Award. Professor Fan has led numerous national research projects and authored extensive monographs and peer-reviewed articles. Ivan Chin Shing FU, registered Architect Hong Kong, has been participating actively in various public platforms in Hong Kong and mainland China, including statutory bodies like the Town Planning Board, Construction Industry Council, Urban Renewal Fund, Enhancing Self-Reliance Through District Partnership Programme and China Green Building Council. Ivan is particularly interested in conservation and sustainability in a social and environmental sense. Among his acclaimed works, the Blue House clinched the highest recognition of the UNESCO Asia-Pacific Awards for Cultural Heritage Conservation with the Award of Excellence. Sunnie Sing Yeung LAU is an Adjunct Associate Professor at both the Chinese University of Hong Kong and the University of Hong Kong, Registered Architect (HKIA/ARB HK, RIBA) specialising in urban regeneration strategies for high-density environments. Her academic work focuses on participatory design methodologies for smart, sustainable cities, notably through the Kowloon East Inclusive Innovation & Growth Initiative (2013-2022), which integrated community engagement with post-industrial site revitalisation. With over 14 years of professional practice, she leads the Hong Kong-based SOS Architecture Urban Design Studio. She was part of the three-person Creator Team for Hong Kong of the Venice Biennale 2024. Jin Zhang is a sustainability-focused urban planner and designer whose research and professional work centre on low-carbon design principles in Asian cities. She received her Master of Urban Design with Distinction from the University of Hong Kong in 2022, and works at the intersection of urban sustainability and environmental responsibility. Her research applies spatial configuration analysis to high-density urban environments, examining how density, form, and connectivity shape environmental performance. Stephen Siu Yu Lau was born and raised in Hong Kong. Received education and professional training in Hong Kong and London, he has devoted thirty years plus to the education of architects and graduated 50+ PhD in Hong Kong and Singapore-retired as a Professor of Architecture from the National University of Singapore. Recently joined the Macau University of Science and Technology as a Distinguished Professor. Whilst an active researcher. He has been practicing as an architect, as well as a consultant on sustainable design and certification, environmental technology-acoustics, daylighting, artificial lighting and carbon auditing. He has been an advocate of green building since the mid-late nineties.