You are previewing International Journal of Data Warehousing and Mining (IJDWM) Volume 10, Issue 1.
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International Journal of Data Warehousing and Mining (IJDWM) Volume 10, Issue 1

Book Description

The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving data.

This issue contains the following articles:

  • BAHUI: Fast and Memory Efficient Mining of High Utility Itemsets Based on Bitmap
  • Deductive Data Warehouses
  • SpyNetMiner: An Outlier Analysis to Tag Elites in Clandestine Social Networks
  • A Perturbation Method Based on Singular Value Decomposition and Feature Selection for Privacy Preserving Data Mining