Articoli correlati a Advances in Mining Complex Data: Modeling and Clustering
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Complex data come from different application contexts. In order of handling and manage them, it is important to define suitable representation models which underly the main data features. Another challenge regards analysis systems and data exploration techniques, which support the whole Knowledge Discovery in Databases (KDD) process. Investigating and solving representation problems for complex data and defining proper algorithms and techniques to extract models, patterns and new information from such data in an effective and efficient way are the main challenges which this thesis aims to face. In particular, two main aspects have been investigated, that are the way in which complex data can be modeled (i.e., data modeling), and the way in which homogeneous groups within complex data can be identified (i.e., data clustering). The application contexts that have been objective of such studies are time series data, uncertain data, text data, and biomedical data.
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L'autore
Giovanni Ponti has been a researcher at ENEA since 2010. He graduated magna cum laude in Computer Engeneering at the University of Calabria in 2005, and obtained his Ph.D. in Computer Engeneering in 2010. His activities concern HPC systems, Cloud Computing and Data Mining. He has coauthored journal articles, conference papers and book chapters.
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Advances in Mining Complex Data: Modeling and Clustering
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Lap Lambert Academic Publishing, 2013
ISBN 10: 3659305227
ISBN 13: 9783659305221
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Condizione: Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In poor condition, suitable as a reading copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,450grams, ISBN:9783659305221. Codice articolo 9380050
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Advances in Mining Complex Data: Modeling and Clustering
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LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659305227
ISBN 13: 9783659305221
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ponti GiovanniGiovanni Ponti has been a researcher at ENEA since 2010. He graduated magna cum laude in Computer Engeneering at the University of Calabria in 2005, and obtained his Ph.D. in Computer Engeneering in 2010. His activities. Codice articolo 5147179
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Advances in Mining Complex Data: Modeling and Clustering
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LAP LAMBERT Academic Publishing Jan 2013, 2013
ISBN 10: 3659305227
ISBN 13: 9783659305221
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Complex data come from different application contexts. In order of handling and manage them, it is important to define suitable representation models which underly the main data features. Another challenge regards analysis systems and data exploration techniques, which support the whole Knowledge Discovery in Databases (KDD) process. Investigating and solving representation problems for complex data and defining proper algorithms and techniques to extract models, patterns and new information from such data in an effective and efficient way are the main challenges which this thesis aims to face. In particular, two main aspects have been investigated, that are the way in which complex data can be modeled (i.e., data modeling), and the way in which homogeneous groups within complex data can be identified (i.e., data clustering). The application contexts that have been objective of such studies are time series data, uncertain data, text data, and biomedical data. 248 pp. Englisch. Codice articolo 9783659305221
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Advances in Mining Complex Data: Modeling and Clustering
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LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659305227
ISBN 13: 9783659305221
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Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Complex data come from different application contexts. In order of handling and manage them, it is important to define suitable representation models which underly the main data features. Another challenge regards analysis systems and data exploration techniques, which support the whole Knowledge Discovery in Databases (KDD) process. Investigating and solving representation problems for complex data and defining proper algorithms and techniques to extract models, patterns and new information from such data in an effective and efficient way are the main challenges which this thesis aims to face. In particular, two main aspects have been investigated, that are the way in which complex data can be modeled (i.e., data modeling), and the way in which homogeneous groups within complex data can be identified (i.e., data clustering). The application contexts that have been objective of such studies are time series data, uncertain data, text data, and biomedical data. Codice articolo 9783659305221
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Immagini fornite dal venditore
Advances in Mining Complex Data: Modeling and Clustering
Editore:
LAP LAMBERT Academic Publishing Jan 2013, 2013
ISBN 10: 3659305227
ISBN 13: 9783659305221
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. Neuware -Complex data come from different application contexts. In order of handling and manage them, it is important to define suitable representation models which underly the main data features. Another challenge regards analysis systems and data exploration techniques, which support the whole Knowledge Discovery in Databases (KDD) process. Investigating and solving representation problems for complex data and defining proper algorithms and techniques to extract models, patterns and new information from such data in an effective and efficient way are the main challenges which this thesis aims to face. In particular, two main aspects have been investigated, that are the way in which complex data can be modeled (i.e., data modeling), and the way in which homogeneous groups within complex data can be identified (i.e., data clustering). The application contexts that have been objective of such studies are time series data, uncertain data, text data, and biomedical data.Books on Demand GmbH, Überseering 33, 22297 Hamburg 248 pp. Englisch. Codice articolo 9783659305221
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Advances in Mining Complex Data: Modeling and Clustering
Editore:
LAP LAMBERT Academic Publishing, 2013
ISBN 10: 3659305227
ISBN 13: 9783659305221
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Da: Mispah books, Redhill, SURRE, Regno Unito
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Paperback. Condizione: Like New. Like New. book. Codice articolo ERICA75836593052276
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