• Probabilistic learning approac...

Treffer: Probabilistic learning approaches for indexing and retrieval with the TREC-2 collection

Title:
Probabilistic learning approaches for indexing and retrieval with the TREC-2 collection
Authors:
FUHR, N, PFEIFER, U, BREMKAMP, C, POLLMANN, M, BUCKLEY, C
Source:
TREC-2: Text retrieval conferenceNIST special publication. (500215):67-74
Publisher Information:
Gaithersburg, MD: National Institute of Standards and Technology, 1994.
Publication Year:
1994
Physical Description:
print, 6 ref
Original Material:
INIST-CNRS
Subject Terms:
Science technology, industry, Sciences et technologies, industries, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Sciences de l'information. Documentation, Information science. Documentation, Systèmes de recherche d'informations. Système de gestion documentaire et d'information, Information retrieval systems. Information and document management system, Systèmes de recherche d'information, Information retrieval systems, Sciences de l'information et de la communication, Information and communication sciences, Système de recherche documentaire. Système de gestion documentaire et d'information, Informatique documentaire, Documentation data processing, Información documental, Acheminement, Routing, Encaminamiento, Algorithme, Algorithm, Algoritmo, Apprentissage, Learning, Aprendizaje, Etude expérimentale, Experimental study, Estudio experimental, Fonction poids, Weight function, Función peso, Modèle probabiliste, Probabilistic model, Modelo probabilista, Optimisation, Optimization, Optimización, Pondération, Weighting, Ponderación, Recherche documentaire, Document retrieval, Recuperación documental, Recherche développement, Research and development, Investigación desarrollo, Régression polynomiale, Polynomial regression, Regresión polinomial, Système recherche, Search system, Sistema investigación, Terme indexation, Indexing term, Término indización, Traitement document, Document processing, Tratamiento documento, Fonction indexation, Indexing function, TREC-2
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Univ. Dortmund, Germany
ISSN:
1048-776X
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=3459611
Rights:
Copyright 1995 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Sciences of information and communication. Documentation

FRANCIS
Accession Number:
edscal.3459611
Database:
PASCAL Archive

Weitere Informationen

In this paper, we describe the applicaion 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 data in order to produce a probabilistic indexing with single terms as well 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 show very good performance for both types of queries.