Title :
Dynamic multi-dimensional models for text warehouses
Author :
Bleyberg, Maria Zamfir ; Ganesh, Karthik
Author_Institution :
Dept. of Comput. & Inf. Sci., Kansas State Univ., Manhattan, KS, USA
fDate :
6/22/1905 12:00:00 AM
Abstract :
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
Keywords :
data models; data warehouses; database indexing; full-text databases; meta data; atomic semantic categories; compound semantic categories; document exploration; dynamic multi-dimensional model; efficiency; index table; meta-snowflake schema; metadata; precision; stored document retrieval; taxonomy; text warehouses; Data warehouses; Databases; Decision making; Environmental management; Information retrieval; Joining processes; Logic; Taxonomy; Text categorization;
Conference_Titel :
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Print_ISBN :
0-7803-6583-6
DOI :
10.1109/ICSMC.2000.886416