Citation-Key:
Fuhr:92b
Title:
Integration of Probabilistic Fact and Text Retrieval
Author(s):
N. Fuhr
Publisher:
ACM
In:
Proceedings of the Fifteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Page(s):
211--222
Year:
1992

Abstract:
In this paper, a model for combining text and fact retrieval is described. A query is a set of conditions, where a single condition is either a text or fact condition. Fact conditions can be interpreted as being vague, thus leading to nonbinary weights for fact conditions with respect to database objects. For text conditions, we use descriptions of the occurrence of terms in documents instead of precomputed indexing weights, thus treating terms similar to attributes. Probabilistic indexing weights for conditions are computed by introducing the notion of correctness (or acceptability) of a condition w.r.t. an object. These indexing weights are used in retrieval for a probabilistic ranking of objects based on the retrieval-with-probabilistic-indexing (RPI) model, for which a new derivation is given here.
Classification(s):
H.3.3, H.2.1
Subject descriptor(s):
DBMIRS, probabilistic retrieval, data models
Keywords:
imprecise data, vague queries, probabilistic retrieval

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