Unsupervised learning in information retrieval using NOW architectures

Authors:
E. F. Combarro;J. Ranilla;R. Mones;N. Vázquez;I. Díaz;E. Montañés
Affiliations:
Artificial Intelligence Center, University of Oviedo, Gijón (Asturias), Spain;Artificial Intelligence Center, University of Oviedo, Gijón (Asturias), Spain;Artificial Intelligence Center, University of Oviedo, Gijón (Asturias), Spain;Artificial Intelligence Center, University of Oviedo, Gijón (Asturias), Spain;Artificial Intelligence Center, University of Oviedo, Gijón (Asturias), Spain;Artificial Intelligence Center, University of Oviedo, Gijón (Asturias), Spain
Venue:
EUROCAST'05 Proceedings of the 10th international conference on Computer Aided Systems Theory
Year:
2005

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Abstract

The efficiency and effectiveness of the retrieval of documents which are relevant to a certain topic or user query can be improved by means of the clustering of similar documents as well as by introducing parallel strategies. In this paper we explore the use of unsupervised learning, using clustering algorithms based on neural networks, as well as the introduction of NOW Architectures, a kind of low-cost parallel architecture, and study the impact on Information Retrieval.