A neural cascade architecture for document retrieval

被引：0
|
作者：
Bouchachia, A [1 ]
Mittermeir, R [1 ]
机构：
[1] Univ Klagenfurt, Dept Informat Syst, A-9020 Klagenfurt, Austria
来源：
PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4 | 2003年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes a fuzzy neural approach adopted for information retrieval. After a thematic analysis of documents that produces two conceptual sets called themes and rhemes, a fuzzy representation is derived. The fuzzy representation reflects the hierarchical nature of texts and suggests the use of type-2 fuzzy sets. It is then translated into a cascade of two neural networks. The first level in this cascade is a fuzzy associative memory network (FAM) which maps rhemes to themes and the second level consists of a fuzzy adaptive resonance theory network (Fuzzy ART) which relates themes to document categories. The approach was experimentally evaluated.
引用
收藏
页码：1915 / 1920
页数：6
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