Dynamic multi-dimensional models for text warehouses
Dynamic multi-dimensional models for text warehouses
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DOI：
10.1109/icsmc.2000.886416
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发表时间：
2000-10
期刊：
影响因子：
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通讯作者：
M. Bleyberg;K. Ganesh
中科院分区：
文献类型：
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作者：
M. Bleyberg;K. Ganesh
介绍了一种适合于建立文本仓库的动态多维模型。维度是嵌入在熟悉的分类法中的原子语义类别。这种文本仓库的方法需要大量的维度，其中一些可能事先不知道。动态多维模型的核心是元雪花模式，它是一个带有索引表的雪花模式。索引表包含由原子语义类别和复合语义类别组成的维度的元数据。存储在仓库中的文档根据分配给它们的语义类别进行检索。这样的文本仓库提高了文档探索的精度和效率。
Introduces a dynamic multi-dimensional model, which is suitable for building text warehouses. The dimensions are atomic semantic categories embedded in a familiar taxonomy. This approach to text warehouses requires a large number of dimensions, some of which may be not known in advance. Central to the dynamic multi-dimensional model is the meta-snowflake schema, which is a snowflake schema with an index table. The index table contains metadata on dimensions consisting of atomic and compound semantic categories. The documents stored in the warehouse are retrieved according to the semantic categories assigned to them. Such a text warehouse increases the precision and efficiency of document exploration.