£110.82

Springer Clustering and Information Retrieval - Book 11

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Description

Explore the essential role of clustering in discovering dense sub-regions within multi-dimension data distributions. This volume, part of the Network Theory and Applications series, provides a deep look into how clustering techniques enhance information retrieval processes. Readers will examine practical uses for clustering, including document grouping, query expansion, document indexing, and the visualization of search results. The text covers a broad range of topics, from fundamental clustering algorithms to evaluation methodologies and system architectures. With technical insights from experts like Baeza-Yates et al., this book describes specific clustering methods for general metrics. It serves as a comprehensive resource for understanding how to apply these algorithms and architectures to modern information retrieval challenges.

Key Features

Covers fundamental clustering algorithms and methodologies for discovering dense data sub-regions.

Explains practical applications in information retrieval such as query expansion and document grouping.

Provides technical details on document indexing and the visualization of search results.

Includes specialized content on clustering methods for general metrics by Baeza-Yates et al.

Discusses various architectures and evaluation methodologies for information retrieval systems.

Part of the Network Theory and Applications series, volume 11, published by Springer.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
30 November 2003
Listed Since
22 December 2006

Barcode

No barcode data available

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