A self-organizing semantic map for information retrieval

Abstract

A neural network's unsupervised learning algorithm, Kohonen's feature map, is applied to constructing a self-organizing semantic map for information retrieval. The semantic map visualizes semantic relationships between input documents, and has properties of economic representation of data with their interrelationships. The potentials of the semantic map include using the map as a retrieval interface for an online bibliographic system. A prototype system that demonstrates this potential is described.