Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development

Innovative Methods and Applications
Erscheinungsjahr 2011
ISBN: 978-1-60566-748-5
Verlag: Information Science Reference

Buch, Englisch, 307 Seiten, Hardback, Format (B × H): 221 mm x 286 mm, Gewicht: 1325 g

Recently, researchers have focused on challenging problems facing the development of data warehousing, knowledge discovery, and data mining applications. ""Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications"" provides a comprehensive analysis on current issues and trends in retrieval expansion. Containing research from leading international experts, this book presents future challenges and opportunities in the field valuable to academicians, researchers, and practitioners.

Autoren/Hrsg.

Nguyen, Tho Manh

Inhaltsverzeichnis

Calendar-based pattern mining Cost-sensitive decision trees Data mining techniques Data warehousing systems Decisional annotations Deploying data warehouses in grids Encrypted network streams Federated data warehouses Multidimensional systems OLAP databases Ranking gradients in multi-dimensional spaces Scalable indexing and storage Spatial data warehouses

Über Autor(innen)

Tho Manh Nguyen received his PhD in information systems from the Vienna University of Technology (September 2005) and currently keeps a postdoctoral research fellowship. He has been awarded Microsoft Student Travel Awards, IBM Europe Student Event Recognition and Outstanding Student Award; Best Paper Award at the 4th IEEE International Conference On Computer Sciences Research; and Best Paper Award at the Information Resources Management Association (IRMA) International Conference (2007). He is a PC member and organizer of many international conferences and workshops such as DaWaK, DAWAM, ARES, SIIK, and CONFENIS and has several publications in international conference proceedings and journals in the field of data warehousing and knowledge discovery. His research interests include data warehousing, data mining and knowledge discovery, business intelligence systems, grid-based knowledge discovery, service-oriented computing, ontology, and semantic management.