Citation-Key:
Fuhr/Buckley:93
Title:
Optimizing Document Indexing and Search Term Weighting Based on Probabilistic Models
Author(s):
N. Fuhr
C. Buckley
In:
Citation-Key:
TREC-1
Title:
The First Text REtrieval Conference (TREC-1)
Editor(s):
D. Harman
Publisher:
National Institute of Standards and Technology Special Publication 500-207
In:
The First Text REtrieval Conference (TREC-1)
Year:
1993

Classification(s):
H.3.3
General terms:
experimentation

BibTeX entry

Page(s):
89--100
Year:
1993

Abstract:
We describe the application of probabilistic indexing and retrieval methods to the TREC material. For document indexing, we apply a description-oriented approach which uses relevance feedback information from previous queries run on the same collection. This method is also very flexible w.r.t. the underlying document representation. In our experiments, we consider single words and phrases and use polynomial functions for mapping the statistical parameters of these terms onto probabilistic indexing weights. Based on these weights, a linear (utility-theoretic) retrieval function is applied when no relevance feedback data is available for the specific query. Otherwise, the retrieval-with-probabilistic-indexing model can be used. The experimental results show excellent performance in both cases, but also indicate possible improvements.
Classification(s):
H.3.3, H.3.1
Subject descriptor(s):
indexing methods, retrieval models
General terms:
experimentation
Keywords:
TREC, description-oriented, probabilistic retrieval

BibTeX entry

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