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OLAP Models for Sequential Data – Current State of Research and Open Problems

  • Łukasz Nienartowicz
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 185)

Abstract

In recent years, sequential data processing has been extensively studied in the research literature. Because of the popularity and peculiarity of this type of data, many systems devoted to storage, sharing and processing of sequential data have been created. The development of this type of systems includes databases with SQLlike languages, data warehouses and OLAP. So far, four models of OLAP cubes for sequential data have been designed: FlowCube, S − OLAP, OLAP on Search Logs, and E − Cube. These models significantly differ from each other. In effect, there is a need to analyze these models and compare their usability. The following analysis reveals advantages and disadvantages of the aforementioned models and discusses possible research issues.

Keywords

Query Language Abstraction Level Large Data Base Invert Index Pattern Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Poznan University of TechnologyPoznanPoland

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