antipole tree indexing graphgrepvf von reforgiato recupero (5 Ergebnisse)

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.

Paperback. Zustand: Like New. Like New. book.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Reforgiato Recupero DiegoDiego Reforgiato is a Researcher at the DIIT of the Univ. of Catania. The support for this fellowship has been given by PROVIDEO, a Marie Curie Grant that Dr. Reforgiato won in 2008. From 4/1/2005 to 5/1/2008.

Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 156 pp. Englisch.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.