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|a Zhang, Jin.
|e author.
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|a Visualization for Information Retrieval
|h [electronic resource] /
|c by Jin Zhang.
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|a 1st ed. 2008.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2008.
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|a XVIII, 294 p. 72 illus., 1 illus. in color.
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|a The Information Retrieval Series,
|x 1387-5264 ;
|v 23
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1 |
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|a Springer eBook Collection
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| 505 |
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|a 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.
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| 520 |
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|a 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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