Self-Organizing Maps Applied to Information Retrieval of Dissertations and Theses from BDTD-UFPE

This paper proposes the application of Self-Organizing Maps (SOM) in the construction of an Information Retrieval System (IRS) to the Digital Library of Theses and Dissertations at Federal University of Pernambuco (BDTD-UFPE). The hypothesis is that the trained SOM and its graphical representation can help the user to obtain a general view of topics discussed in the document collection and also to perceive the similarity among documents, topics and graduate programs´ knowledge areas and subjects. We present the system architecture and implementation´s issues and evaluate the hypothesis through experimentation. The unsupervised organization performance of the proposed system was measured in terms of text categorization effectiveness and visual inspection of categories´ distribution over graphics about trained SOM. The experimental results show that the proposed system generates relevant document map and confirms the hypothesis.