Scaling relationships in back-propagation learning
Complex Systems
Neural networks: algorithms, applications, and programming techniques
Neural networks: algorithms, applications, and programming techniques
The effectiveness of GIOSS for the text database discovery problem
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Machine Learning as an Experimental Science
Machine Learning
Hierarchically Classifying Documents Using Very Few Words
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Determining Text Databases to Search in the Internet
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Generalizing GlOSS to Vector-Space Databases and Broker Hierarchies
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Neural Net Agent for Discovering Text Databases on the Web
ADBIS '99 Proceedings of the Third East European Conference on Advances in Databases and Information Systems
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
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Agent approaches has been increasingly used within information technology to describe various computational entities. Especially, due to the proliferation of readily available text databases on the Web, agents have been often developed as the computational entities for discovering useful text databases on the Web. In this paper, we motivate the need for the hierarchical organization of those agents. The motivation is based on our experiences with the neural net agents for the text database discovery and an analysis of the tradeoff between the benefit of the hierarchical organization of agents and multi-agent coordination overhead. We first introduce the neural net agent and then motivate our multi-agent approach based on the hierarchical organization of neural net agents both analytically and experimentally.