Treffer: The university of Massachusetts TIPSTER project
Title:
The university of Massachusetts TIPSTER project
Authors:
Source:
TREC-1: Text Retrieval ConferenceNIST special publication. (500207):101-105
Publisher Information:
Gaithersburg, MD: National Institute of Standards and Technology, 1993.
Publication Year:
1993
Physical Description:
print, 5 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, Traitement et recherche de l'information, Information processing and retrieval, Structure et analyse des documents et de l'information, Information and document structure and analysis, Analyse des contenus, Content analysis, Indexation. Classification. Résumé. Synthèses, Indexing. Classification. Abstracting. Syntheses, Sciences de l'information et de la communication, Information and communication sciences, Traitement et recherche d'information, Informatique documentaire, Documentation data processing, Información documental, Analyse linguistique, Linguistic analysis, Análisis linguístico, Analyse statistique, Statistical analysis, Análisis estadístico, Apprentissage, Learning, Aprendizaje, Essai, Test, Ensayo, Formulation question, Query formulation, Formulación pregunta, Inférence, Inference, Inferencia, Langage naturel, Natural language, Lenguaje natural, Modèle, Models, Modelo, Phrase, Sentence, Frase, Recherche documentaire, Document retrieval, Recuperación documental, Recherche développement, Research and development, Investigación desarrollo, Résultat expérimental, Experimental result, Resultado experimental, Rétroaction, Feedback regulation, Retroacción, Système documentaire, Document retrieval system, Sistema recuperación documental, Texte intégral, Full text, Texto completo, Traitement langage, Language processing, Tratamiento lenguaje, Relevance feedback, TIPSTER, TREC
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Univ. Massachusetts, computer sci. dep., Amherst MA 01003, United States
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.3772373
Database:
PASCAL Archive
Weitere Informationen
Our general approach to achieving these goals has been to use improved representations of text and information needs in the framework of a new model of retrieval. Retrieval (and routing) is viewed as a probabilistic inference process which «compares» text representations based on different forms of linguistic and statistical evidence to representations of information needs based on similar evidence from natural language queries and user interaction. New techniques for learning (relevance feedback) and extracting term relationships from text are also being studied.