PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Sebastiani F. Total knowledge and partial knowledge in logical models of information retrieval. In: Foundations of Intelligent Systems. 11th International Symposium, ISMIS'99. Proceedings (Warsaw (Poland), June 8-11 1999). Proceedings, vol. 1609 pp. 133 - 149. Z.W. Ras and A. Skowron (eds.). (Lecture Notes in Artificial Intelligence). Springer, 1999.
 
 
Abstract
(English)
V~% here expand on a previous paper concerning the role of logic in information retrieval (IR) modelling.. In that paper, among other things, we had pointed out how differenV ways of understanding the contribution of logic to IR have sprung from the (always unstated adherence to either the total or the partial'knowledge assumption. Here we make our analysis more precise by relat.ing this dichotomy to the notion of vividness, as used in knowledge iepresentation, and to another dichotomy which has had a profound influence in DB theory, namely the distinction between the proof-theoretic and the model-theoretic views of a database, spelled out by Reiter in his "logical reconstruction of database theory". We show that precisely the same distinction can be applied to logical models of IR developed so far. The strengths and weaknesses of ~he adopti~,~ of either approach in logical models of [R are discussed.
Subject Information retrieval
H.3.3 Information search and retrieval


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