Zitationsschlüssel:
Fuhr/etal:94
Titel:
Probabilistic Learning Approaches for Indexing and Retrieval with the TREC-2 Collection
Autor(en):
N. Fuhr
U. Pfeifer
C. Bremkamp
M. Pollmann
C. Buckley
In:
Zitationsschlüssel:
TREC-2
Titel:
The Second Text REtrieval Conference (TREC-2)
Herausgeber:
D. Harman
Verlag:
National Institute of Standards and Technology
In:
The Second Text REtrieval Conference (TREC-2)
Jahr:
1994

Klassifikation(en):
H.3.3
Allgemeine Terme:
experimentation

BibTeX-Eintrag

Seite(n):
67--74
Jahr:
1994

Zusammenfassung:
In this paper, we describe the application of probabilistic models for indexing and retrieval with the TREC-2 collection. This database consists of about a million documents (2 gigabytes of data) and 100 queries (50 routing and 50 adhoc topics). For document indexing, we use a description-oriented approach which exploits relevance feedback data in order to produce a probabilistic indexing with single terms as well as with phrases. With the adhoc queries, we present a new query term weighting method based on a training sample of other queries. For the routing queries, the RPI model is applied which combines probabilistic indexing with query term weighting based on query-specific feedback data. The experimental results of our approach show very good performance for both types of queries.
Klassifikation(en):
H.3.3, G.1.2, H.3.1
Subjektdeskriptor(en):
least squares approximation, indexing methods, retrieval models
Schlüsselwörter:
query expansion, probabilistic models

BibTeX-Eintrag

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