Title :
Structured document labeling and rule extraction using a new recurrent fuzzy-neural system
Author :
Palmero, G. I Sainz ; Dimitriadis, Y.A.
Author_Institution :
Sch. of Ind. Eng., Valladolid Univ., Spain
Abstract :
Proposes an approach to the problem of logical labeling in structured documents, employing a new recurrent neuro-fuzzy system called RFasArt (Recurrent Fuzzy Adaptive System, ART-based). RFasArt preserves the fine characteristics, such as modularity, stability and flexibility, of its predecessors Fuzzy ARTMAP and FasArt. In this paper, the documents are considered as pseudo-temporal sequences, and context information is exploited in an integrated form. Two working prototypes for a MIME-based mailing system and for a digital library were tested with over 90% of the recognition rate and less ambiguous decisions than in the previous systems. A manageable knowledge base was constructed using fuzzy rules that were easily interpretable by human users, and examples of rule creation and fusion are shown
Keywords :
ART neural nets; adaptive systems; digital libraries; document image processing; electronic mail; fuzzy neural nets; image recognition; knowledge based systems; recurrent neural nets; software prototyping; ART-based recurrent fuzzy adaptive system; MIME-based mailing system; RFasArt; ambiguous decisions; context information; digital library; flexibility; interpretable fuzzy rules; knowledge base; modularity; pseudo-temporal sequences; recognition rate; recurrent fuzzy-neural system; recurrent neuro-fuzzy system; rule creation; rule extraction; rule fusion; stability; structured document labeling; working prototypes; Adaptive systems; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Knowledge management; Labeling; Prototypes; Software libraries; Stability; System testing;
Conference_Titel :
Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on
Conference_Location :
Bangalore
Print_ISBN :
0-7695-0318-7
DOI :
10.1109/ICDAR.1999.791754
