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ANTIPOLE TREE INDEXING AND GRAPHGREPVF: DATA STRUCTURES AND ALGORITHMS FOR OPTIMIZATION AND SEARCHING PROBLEMS IN METRIC SPACES AND GRAPHS - Softcover
Inhaltsangabe
There has been increasing interest in building search/index structures to perform similarity search over high-dimensional data, e.g., image databases, document collections, time-series databases, and genome databases. A similarity search problem involves a collection of objects (e.g., documents, images) which are characterized by a collection of relevant features and represented as points in a high-dimensional attribute space. The first part of this book will present a new hierarchical clustering algorithm called Antipole Clustering. The algorithm partitions the set of data objects in clusters such that each one has diameter approximately less than a given value. The algorithm returns a tree structure called Antipole Tree in which the leaves are the final clusters. The second part of this book will present, GraphGrepVF, an application-independent method for querying a database of graphs in order to find all the occurrences of a given subgraph. Many applications in industry, science and engineering share this problem, and increasing the size of the database requires efficient structure searching algorithms.
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There has been increasing interest in building search/index structures to perform similarity search over high-dimensional data, e.g., image databases, document collections, time-series databases, and genome databases. A similarity search problem involves a collection of objects (e.g., documents, images) which are characterized by a collection of relevant features and represented as points in a high-dimensional attribute space. The first part of this book will present a new hierarchical clustering algorithm called Antipole Clustering. The algorithm partitions the set of data objects in clusters such that each one has diameter approximately less than a given value. The algorithm returns a tree structure called Antipole Tree in which the leaves are the final clusters. The second part of this book will present, GraphGrepVF, an application-independent method for querying a database of graphs in order to find all the occurrences of a given subgraph. Many applications in industry, science and engineering share this problem, and increasing the size of the database requires efficient structure searching algorithms.
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ANTIPOLE TREE INDEXING AND GRAPHGREPVF
Verlag:
LAP LAMBERT Academic Publishing Jun 2010, 2010
ISBN 10: 383836838X
ISBN 13: 9783838368382
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Taschenbuch. Zustand: Neu. Neuware -There has been increasing interest in building search/index structures to perform similarity search over high-dimensional data, e.g., image databases, document collections, time-series databases, and genome databases. A similarity search problem involves a collection of objects (e.g., documents, images) which are characterized by a collection of relevant features and represented as points in a high-dimensional attribute space. The first part of this book will present a new hierarchical clustering algorithm called Antipole Clustering. The algorithm partitions the set of data objects in clusters such that each one has diameter approximately less than a given value. The algorithm returns a tree structure called Antipole Tree in which the leaves are the final clusters. The second part of this book will present, GraphGrepVF, an application-independent method for querying a database of graphs in order to find all the occurrences of a given subgraph. Many applications in industry, science and engineering share this problem, and increasing the size of the database requires efficient structure searching algorithms.Books on Demand GmbH, Überseering 33, 22297 Hamburg 156 pp. Englisch. Artikel-Nr. 9783838368382
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