
Visualization for Information Retrieval
By: Jin Zhang, W. B. Croft (Foreword by), Edie Rasmussen (Foreword by)
Hardcover | 16 November 2007
At a Glance
312 Pages
23.5 x 15.88 x 1.91
Hardcover
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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.
Industry Reviews
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)
| Information Retrieval and Visualization | p. 1 |
| Visualization | p. 3 |
| Definition | p. 3 |
| Scientific visualization and information visualization | p. 3 |
| Information retrieval | p. 4 |
| Browsing vs. query searching | p. 5 |
| Information at micro-level and macro-level | p. 7 |
| Spatial Characteristics of information space | p. 8 |
| Spatial characteristics of browsing | p. 10 |
| Perceptual and cognitive perspectives of visualization | p. 11 |
| Perceptual perspective | p. 11 |
| Cognitive perspective | p. 12 |
| Visualization for information retrieval | p. 13 |
| Rationale | p. 13 |
| Three information retrieval visualization paradigms | p. 16 |
| Procedures of establishing an information retrieval visualization model | p. 16 |
| Summary | p. 20 |
| Information Retrieval Preliminaries | p. 21 |
| Vector space model | p. 22 |
| Term weighting methods | p. 24 |
| Stop words | p. 25 |
| Inverse document frequency | p. 25 |
| The Salton term weighting method | p. 26 |
| Another term weighting method | p. 26 |
| Probability term weighting method | p. 26 |
| Similarity measures | p. 27 |
| Inner product similarity measure | p. 28 |
| Dice co-efficient similarity measure | p. 28 |
| The Jaccard co-efficient similarity measure | p. 28 |
| Overlap co-efficient similarity measure | p. 29 |
| Cosine similarity measure | p. 29 |
| Distance similarity measure | p. 30 |
| Angle-distance integrated similarity measure | p. 32 |
| The Pearson r correlation measure | p. 33 |
| Information retrieval (evaluation) models | p. 34 |
| Direction-based retrieval (evaluation) model | p. 34 |
| Distance-based retrieval (evaluation) model | p. 35 |
| Ellipse retrieval (evaluation) model | p. 36 |
| Conjunction retrieval (evaluation) model | p. 36 |
| Disjunction evaluation model | p. 38 |
| The Cassini oval retrieval (evaluation) model | p. 39 |
| Clustering algorithms | p. 40 |
| Non-hierarchical clustering algorithm | p. 42 |
| Hierarchical clustering algorithm | p. 43 |
| Evaluation of retrieval results | p. 45 |
| Summary | p. 46 |
| Visualization Models for Multiple Reference Points | p. 47 |
| Multiple references points | p. 48 |
| Model for fixed multiple reference points | p. 49 |
| Models for movable multiple reference points | p. 52 |
| Description of the original VIBE algorithm | p. 52 |
| Discussions about the model | p. 59 |
| Model for automatic reference point rotation | p. 66 |
| Definition of the visual space | p. 67 |
| Rotation of a reference point | p. 69 |
| Implication of information retrieval | p. 70 |
| Summary | p. 72 |
| Euclidean Spatial Characteristic Based Visualization Models | p. 73 |
| Euclidean space and its characteristics | p. 73 |
| Introduction to the information retrieval evaluation models | p. 75 |
| The distance-angel-based visualization model | p. 79 |
| The visual space definition | p. 79 |
| Visualization for information retrieval evaluation models | p. 81 |
| The angle-angle-based visualization model | p. 88 |
| The visual space definition | p. 88 |
| Visualization for information retrieval evaluation models | p. 89 |
| The distance-distance-based visualization model | p. 97 |
| The visual space definition | p. 97 |
| Visualization for information retrieval evaluation models | p. 99 |
| Summary | p. 104 |
| Kohonen Self-Organizing Map-An Artificial Neural Network | p. 107 |
| Introduction to neural networks | p. 107 |
| Definition of neural network | p. 108 |
| Characteristics and structures of neuron network | p. 109 |
| Kohonen self-organizing maps | p. 111 |
| Kohonen self-organizing map structures | p. 112 |
| Learning processing of the SOM algorithm | p. 113 |
| Feature map labeling | p. 119 |
| The SOM algorithm description | p. 120 |
| Implication of the SOM in information retrieval | p. 121 |
| Summary | p. 124 |
| Pathfinder Associative Network | p. 127 |
| Pathfinder associative network properties and descriptions | p. 128 |
| Definitions of concepts and explanations | p. 128 |
| The algorithm description | p. 131 |
| Graph layout method | p. 136 |
| Implications on information retrieval | p. 137 |
| Author co-citation analysis | p. 137 |
| Term associative network | p. 139 |
| Hyperlink | p. 140 |
| Search in Pathfinder associative networks | p. 141 |
| Summary | p. 142 |
| Multidimensional Scaling | p. 143 |
| MDS analysis method descriptions | p. 144 |
| Classical MDS | p. 144 |
| Non-metric MDS | p. 151 |
| Metric MDS | p. 157 |
| Implications of MDS techniques for information retrieval | p. 158 |
| Definitions of displayed objects and proximity between objects | p. 158 |
| Exploration in a MDS display space | p. 160 |
| Discussion | p. 161 |
| Summary | p. 163 |
| Internet Information Visualization | p. 165 |
| Introduction | p. 165 |
| Internet characteristics | p. 165 |
| Internet information organization and presentation methods | p. 166 |
| Internet information utilization | p. 168 |
| Challenges of the internet | p. 170 |
| Internet information visualization | p. 171 |
| Visualization of internet information structure | p. 172 |
| Internet information seeking visualization | p. 180 |
| Visualization of web traffic information | p. 183 |
| Discussion history visualization | p. 188 |
| Summary | p. 189 |
| Ambiguity in Information Visualization | p. 191 |
| Ambiguity and its implication in information visualization | p. 192 |
| Reason of ambiguity in information visualization | p. 192 |
| Implication of ambiguity for information visualization | p. 193 |
| Ambiguity analysis in information retrieval visualization models | p. 194 |
| Ambiguity in the Euclidean spatial characteristic based information models | p. 194 |
| Ambiguity in the multiple reference point based information visualization models | p. 202 |
| Ambiguity in the Pathfinder network | p. 207 |
| Ambiguity in SOM | p. 209 |
| Ambiguity in MDS | p. 210 |
| Summary | p. 211 |
| The Implication of Metaphors in Information Visualization | p. 215 |
| Definition, basic elements, and characteristics of a metaphor | p. 215 |
| Cognitive foundation of metaphors | p. 218 |
| Mental models, metaphors, and human computer interaction | p. 219 |
| Metaphors in human computer interaction | p. 219 |
| Mental models | p. 220 |
| Mental models in HCI | p. 220 |
| Metaphors in information visualization retrieval | p. 223 |
| Rationales for using metaphors | p. 223 |
| Metaphorical information retrieval visualization environments | p. 225 |
| Procedures and principles for metaphor application | p. 231 |
| Procedure for metaphor application | p. 231 |
| Guides for designing a good metaphorical visual information retrieval environment | p. 232 |
| Summary | p. 236 |
| Benchmarks and Evaluation Criteria for Information Retrieval Visualization | p. 239 |
| Information retrieval visualization evaluation | p. 239 |
| Benchmarks and evaluation standards | p. 243 |
| Factors affecting evaluation standards | p. 243 |
| Principles for developing evaluation benchmarks | p. 244 |
| Four proposed categories for evaluation criteria | p. 244 |
| Descriptions of proposed benchmarks | p. 246 |
| Summary | p. 253 |
| Afterthoughts | p. 255 |
| Introduction | p. 255 |
| Comparisons of the introduced visualization models | p. 257 |
| Issues and challenges | p. 260 |
| Summary | p. 268 |
| Bibliography | p. 269 |
| Index | p. 287 |
| Table of Contents provided by Ingram. All Rights Reserved. |
ISBN: 9783540751472
ISBN-10: 3540751475
Series: Information Retrieval
Published: 16th November 2007
Format: Hardcover
Language: English
Number of Pages: 312
Audience: College, Tertiary and University
Publisher: Springer Nature B.V.
Country of Publication: DE
Dimensions (cm): 23.5 x 15.88 x 1.91
Weight (kg): 0.64
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This product is categorised by
- Non-FictionLibrary & Info Sciences
- Non-FictionComputing & I.T.Operating Systems
- Non-FictionComputing & I.T.Graphical & Digital Media Applications
- Non-FictionComputing & I.T.DatabasesInformation Retrieval
- Non-FictionComputing & I.T.Computer Programming & Software DevelopmentSoftware Engineering
- Non-FictionComputing & I.T.Information Technology General Issue
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- Non-FictionComputing & I.T.Computer ScienceHuman-Computer Interaction




















