Una soggettazione automatica di letteratura grigia con algoritmi di rete neurale. Due esperimenti: ICAS e ILC.
Authors: Lanza C., Pardelli G.
Autors Affiliation: Istituto di Chimica Analitica Strumentale (ICAS) CNR, Pisa
Istituto di Linguistica Computazionale (ILC) CNR, Pisa
Abstract: The aim of this work is to create an automatic subject classification of grey literature documents using an artificial neural
network. In particular, a software simulator of neural network with back-propagation learning scheme was used; training of the network was carried out on around 300 documents. The prototype developed follows the steps which were performed during the learning, the processing and the network querying phase. The analysis of the final tests provides targets to be referred to the percentage of document classification
error for each subject. From this data it is possible to evince possible document-subject correlations and/or subject-subject correlations in order to construct a relational Database of the scientific documents available at the Institute of Computational Linguistics and at the Institute of Instrumental Analitical Chemistry of the Italian National Research Council.
Conference title: La Letteratura grigia: politica e pratica. 3° Convegno nazionale – Istituto Superiore di Sanita’ Roma, 25-26 novembre 1999
More Information: Book: Atti a cura di V. Alberani e P. De Castro. ISTISAN CONGRESSI 67 (2000), p. 52-56 – ISSN 0393-5620KeyWords: Data Mining; Artificial Neural Network; IT for Library