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The growing complexity and volume of modern databases make it increasingly important for researchers and practitioners involved with association rule mining to make sense of the information they contain. Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection provides readers with an in-depth compendium of current issues, trends, and technologies in association rule mining. Covering a comprehensive range of topics, this book discusses underlying frameworks, mining techniques, interest metrics, and real-world application domains within the field.
Acerca de los autores:
Yun Sing Koh is currently a lecturer in computer science at Auckland University of Technology (New Zealand). After completing a bachelor's degree in computer science and master’s degree in software engineering at the University of Malaya, she went on to do her PhD in computer science in Otago, New Zealand. Her current research interests include data mining, machine learning, and information retrieval.
Nathan Rountree is a lecturer in computer science at the University of Otago (Dunedin, New Zealand), where he teaches papers on databases, data structures and algorithms, and Web development. He holds a bachelor's degree in music, a postgraduate diploma in computer science, and a PhD in computer science, all from Otago. His research interests include computer science education, artificial neural networks, and collaborative filtering.
Título: RARE ASSOCIATION RULE MINING AND KNOWLEDGE ...
Editorial: Information Science Reference
Año de publicación: 2009
Encuadernación: Encuadernación de tapa dura
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Librería: Basi6 International, Irving, TX, Estados Unidos de America
Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Nº de ref. del artículo: ABEOCT25-180025
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The growing complexity and volume of modern databases make it important for researchers and practitioners involved with association rule mining to make sense of the information they contain. This book provides readers with a compendium of issues, trends, an. Nº de ref. del artículo: 4237481
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Buch. Condición: Neu. Rare Association Rule Mining and Knowledge Discovery | Technologies for Infrequent and Critical Event Detection | Yun Sing Koh (u. a.) | Buch | Gebunden | Englisch | 2010 | Information Science Reference | EAN 9781605667546 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 101581561
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Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The growing complexity and volume of modern databases make it increasingly important for researchers and practitioners involved with association rule mining to make sense of the information they contain. Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection provides readers with an in-depth compendium of current issues, trends, and technologies in association rule mining. Covering a comprehensive range of topics, this book discusses underlying frameworks, mining techniques, interest metrics, and real-world application domains within the field. Nº de ref. del artículo: 9781605667546
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