Abstract
Data warehouse is an information provider that collects necessary data from individual source databases to support the analytical processing of decision-support functions. Recently, research about the indexing technologies of data warehousing has been proposed to help efficient on-line analytical processing (OLAP). In the past decades, some novel indexing technologies of data warehousing were proposed to retrieve the information precisely. However, the concept of similarity indexing technology in the increasingly larger data warehousing was seldom been discussed. In this paper, the performance issue of approximation indexing technology in the data warehousing is discussed and a new similarity indexing method, called bit-wise indexing method, and the corresponding efficient algorithms are proposed for retrieving the similar cases of a case-based reasoning system using a data warehouse to be the storage space. Some experiments are made for comparing the performance with two other methods and the results show the efficiency of the proposed method.
This work was supported by Ministry of Education and National Science Council of the Republic of China under Grand No. 89-E-FA04-1-4, High Confidence Information Systems.
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Chen, WC., Tseng, SS., Chang, LP., Jiang, MF. (2001). A Similarity Indexing Method for the Data Warehousing - Bit-Wise Indexing Method. In: Cheung, D., Williams, G.J., Li, Q. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2001. Lecture Notes in Computer Science(), vol 2035. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45357-1_56
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DOI: https://doi.org/10.1007/3-540-45357-1_56
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