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Relational databases excel at storing large amounts of certain types of data, but are less effective for textual information storage and retrieval because documents do not readily translate into traditional database schema. Eight chapters by international experts explore emerging methods to meet this challenge: e.g., a Document Object Model to generate hypertext documents; automatic text categorization; metadata (data about the text), and databases specifically designed to store and mine text. A case study focuses on cooperative document management in healthcare. Chin is in the Information Systems department at Virginia Commonwealth U. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Text Databases and Document Management: Theory and Practice
by Chin, Amita Goyal Chin
The ability of relational databases to store and manage large amounts of limited data types is well proven, but the basics of representing textual information and its subsequent retrieval in a meaningful fashion still provides many challenges. This is because documents do not easily map to traditional database solutions. The primary objective of Text Databases
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The ability of relational databases to store and manage large amounts of limited data types is well proven, but the basics of representing textual information and its subsequent retrieval in a meaningful fashion still provides many challenges. This is because documents do not easily map to traditional database solutions. The primary objective of Text Databases and Document Management: Theory and Practice is to provide a focal point for concrete theories and practices in the handling of textual data as well as documents as a whole.
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Product Details
- ISBN-13:
- 9781878289933
- Publisher:
- IGI-Global
- Publication date:
- 01/28/2001
- Pages:
- 256
- Product dimensions:
- 7.06(w) x 10.09(h) x 0.58(d)
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