Treffer: Learned vector-space models for document retrieval
Title:
Learned vector-space models for document retrieval
Authors:
Source:
TREC-2 : text retrieval conferenceInformation processing & management. 31(3):419-429
Publisher Information:
Oxford: Elsevier Science, 1995.
Publication Year:
1995
Physical Description:
print, 17 ref
Original Material:
INIST-CNRS
Subject Terms:
Information and communication sciences, Sciences de l'information communication, Documentation, Computer science, Informatique, 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, Apprentissage latent, Latent learning, Aprendizaje latente, Contexte, Context, Contexto, Dispositif expérimental, Experimental device, Dispositivo experimental, Essai, Test, Ensayo, Evaluation système, System evaluation, Evaluación sistema, Expérimentation, Experimentation, Experimentación, Extension, Extensión, Modèle, Models, Modelo, Système documentaire, Document retrieval system, Sistema recuperación documental, LSI (Latent Semantic Indexing), MatchPlus, Modèle espace vectoriel, Vector space model, TREC-2 (Text Retrieval Conference)
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
HNC Inc., San Diego CA 91121, United States
ISSN:
0306-4573
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
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.3601538
Database:
PASCAL Archive
Weitere Informationen
Discusses two different approaches to radical extensions of the vector space model. Bellcore's Latent Semantic Indexing (LSI) and MatchPlus examine the similarity of the contexts in which words appear and create a features space representation in which words that occur in similar contexts have vector representation near each other.