Treffer: Query improvement in information retrieval using genetic algorithms. A report on the experiments of the TREC project
Title:
Query improvement in information retrieval using genetic algorithms. A report on the experiments of the TREC project
Authors:
Source:
TREC-1: Text Retrieval ConferenceNIST special publication. (500207):31-58
Publisher Information:
Gaithersburg, MD: National Institute of Standards and Technology, 1993.
Publication Year:
1993
Physical Description:
print, 19 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, Recherche développement, Research and development, Investigación desarrollo, Algorithme adaptatif, Adaptive algorithm, Algoritmo adaptativo, Espace vectoriel, Vector space, Espacio vectorial, Essai, Test, Ensayo, Evaluation système, System evaluation, Evaluación sistema, Implémentation, Implementation, Ejecución, Indexation automatique, Automatic indexing, Indización automática, Mesure de distance, Distance measurement, Medición distancia, Modèle, Models, Modelo, Prototype, Prototipo, Prétraitement, Pretreatment, Pretratamiento, Recherche documentaire, Document retrieval, Recuperación documental, Représentation par terme indexation, Search pattern, Representación por término indexación, Traitement document, Document processing, Tratamiento documento, Algorithme génétique, Genetic algorithm, Relevance feedback, TREC, Traitement question, Question processing
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Univ. Pittsburg, school library information sci., dep. information sci., Pittsburgh, United Kingdom
ISSN:
1048-776X
Rights:
Copyright 1994 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
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
FRANCIS
Accession Number:
edscal.3772379
Database:
PASCAL Archive
Weitere Informationen
We have been developing an adaptive method using genetic algorithms to modify user queries, based on relevance judgments. This algorithm was adapted for the Text Retrieval Conference (TREC). The method is shown to be applicable to large text collections, where more relevant documents are presented to users in the genetic modification. The algorithm also shows some interesting phenomena, such as parallel searching. Further studies are planned to adjust the system parameters to improve its effectiveness.