Probabilistic Information Retrieval as Combination of Abstraction, Inductive Learning and Probabilistic Assumptions

Zitationsschlüssel:

Fuhr/Pfeifer:94

Titel:

Probabilistic Information Retrieval as Combination of Abstraction, Inductive Learning and Probabilistic Assumptions

Autor(en):

N. Fuhr

U. Pfeifer

Journal:

ACM Transactions on Information Systems

Ausgabe:

12

Nummer:

1

Seite(n):

92--115

Jahr:

1994

Zusammenfassung:

We show that former approaches in probabilistic information retrieval are based on one or two of the three concepts abstraction, inductive learning and probabilistic assumptions, and we propose a new approach which combines all three concepts. This approach is illustrated for the case of indexing with a controlled vocabulary. For this purpose, we describe a new probabilistic model first, which is then combined with logistic regression, thus yielding a generalization of the original model. Experimental results for the pure theoretical model as well as for heuristic variants are given. Furthermore, linear and logistic regression are compared.

Klassifikation(en):

H.3.3

Subjektdeskriptor(en):

retrieval models

Schlüsselwörter:

probabilistic retrieval

BibTeX-Eintrag

Volltext als PS