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Using rough sets to construct sense type decision trees for text categorization

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2 Author(s)
Bleyberg, M.Z. ; Comput. & Inf. Sci. Dept., Kansas State Univ., Manhattan, KS, USA ; Elumalai, A.

Accurate text categorization is needed for efficient and effective text retrieval, search and filtering. Finding appropriate categories and manually assigning them to existing documents is very laborious. The paper shows a simple procedure for automatic extraction of atomic sense types (semantic categories) from documents based on rough sets. The atomic sense types are nodes of a sense type decision tree, which represents a taxonomy

Published in:

IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th  (Volume:1 )

Date of Conference:

25-28 July 2001