Information Retrieval Systems using an Associative Conceptual Space
Jan van den Berg, Martijn J. Schuemie · 1999
An AI-based retrieval system inspired by the WEBSOM-algorithm is proposed. Contrary to the WEBSOM however, we introduce a system using only the index of every document. The knowledge extraction process results into a so-called Associative Conceptual Space where the words as found in the documents are organised using a Hebbian-type of (un)learning. Next, 'concepts ' (i.e.word-clusters) are identified using the SOM-algorithm. Thereupon, each document is characterised by comparing the concepts found in it, to those present in the concept space. Applying the characterisations, all documents can be clustered such that semantically similar documents lie close together on a Self-Organising Map. 1.