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Data Management in Three-Dimensional Structures
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Author(s): Xiong Wang (California State University at Fullerton, USA)
Copyright: 2005
Pages: 5
Source title:
Encyclopedia of Data Warehousing and Mining
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-59140-557-3.ch044
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Abstract
Data management in its general term refers to activities that involve the acquisition, storage, and retrieval of data. Traditionally, information retrieval is facilitated through queries, such as exact search, nearest neighbor search, range search, etc. In the last decade, data mining has emerged as one of the most dynamic fields in the frontier of data management. Data mining refers to the process of extracting useful knowledge from the data. Popular data mining techniques include association rule discovery, frequent pattern discovery, classification, and clustering. In this chapter, we discuss data management in a specific type of data i.e., three-dimensional structures. While research on text and multimedia data management has attracted considerable attention and substantial progress has been made, data management in three-dimensional structures is still in its infancy (Castelli & Bergman, 2001; Paquet & Rioux, 1999). Data management in 3D structures raises several interesting problems: 1. Similarity search 2. Pattern discovery 3. Classification 4. Clustering
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