Citation-Key:
Fuhr/Pfeifer:94
Title:
Probabilistic Information Retrieval as Combination of Abstraction, Inductive Learning and Probabilistic Assumptions
Author(s):
N. Fuhr
U. Pfeifer
Journal:
ACM Transactions on Information Systems
Volume:
12
Number:
1
Page(s):
92--115
Year:
1994

Abstract:
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.
Classification(s):
H.3.3
Subject descriptor(s):
retrieval models
Keywords:
probabilistic retrieval

BibTeX entry

Fulltext as PS