Title :
A new approach to hybrid SOM implementations for text classification
Author :
Gunther, Paul ; Chen, Phoebe
Author_Institution :
Cooperative Inf. Syst. Res. Centre, Queensland Univ. of Technol., Brisbane, Qld., Australia
Abstract :
This paper analyses several recent treatises on hybridised self-organising map (SOM) theory. Each article proposes a solution to expedite the SOM mapping process and provides more accurate results within a shorter response time via hybridisation: including utilisation of Bayesian classification techniques; an interactive associative search and exploration tool; and the use of a hierarchical organization of tiered SOM´s with input derived via auto-associative feedforward neural network technology. In this paper, we propose that an amalgamation of SOM and association rule theory may hold the key to a more generic solution, less reliant on initial supervision and redundant user interaction. The results of clustering stem words from text documents could be utilised to derive association rules which designate the applicability of documents to the user. A four stage process is consequently detailed, demonstrating a generic example of how a graphical derivation of associations may be derived from a repository of text documents, or even a set of synopses of many such repositories.
Keywords :
Bayes methods; data mining; document handling; feedforward neural nets; pattern classification; search problems; self-organising feature maps; Bayesian classification; association rule theory; data mining; feedforward neural network; interactive associative search; redundant user interaction; self organising map; text classification; text mining; Australia; Fuzzy systems; Information systems; Text analysis; Text categorization; Topology; Visualization;
Conference_Titel :
Fuzzy Systems, 2001. The 10th IEEE International Conference on
Print_ISBN :
0-7803-7293-X
DOI :
10.1109/FUZZ.2001.1009119