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International Journal of Data Warehousing and Mining (IJDWM) Volume 11, Issue 3

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:

  • Efficient Compression and Storage of XML OLAP Cubes
  • Understanding the SNN Input Parameters and How They Affect the Clustering Results
  • Resource Constrained Data Stream Clustering with Concept Drifting for Processing Sensor Data
  • An OLAM Operator for Multi-Dimensional Shrink
  • Identifying and Analyzing Popular Phrases Multi-Dimensionally in Social Media Data