Serviceeinschränkungen vom 12.-22.02.2026 - weitere Infos auf der UB-Homepage

Treffer: Evaluating retrieval performance given database and query characteristics : analytic determination of performance surfaces

Title:
Evaluating retrieval performance given database and query characteristics : analytic determination of performance surfaces
Authors:
Source:
Evaluation of information retrieval systemsJournal of the American Society for Information Science. 47(1):95-105
Publisher Information:
New York, NY: John Wiley & Sons, 1996.
Publication Year:
1996
Physical Description:
print, 33 ref
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Univ. North Carolina, Chapel Hill NC 27599-3360, United States
ISSN:
0002-8231
Rights:
Copyright 1996 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.3012866
Database:
PASCAL Archive

Weitere Informationen

An analytic method of information retrieval and filtering evaluation can quantitatively predict the expected number of documents examined in retrieving a relevant document. It also allows researchers and practitioners to qualitatively understand how varying different estimates of query parameter values affects retrieval performance. The incorporation of relevance feedback to increase our knowledge about the parameters of relevant documents and the robustness of parameter estimates is modeled. Single term and two term independence models, as well as a complete term dependence model, are developed. An economic model of retrieval performance may be used to study the effects of database size and to provide analytic answers to questions comparing retrieval from small and large databases, as well as questions about the number of terms in a query. Results are presented as a performance surface, a three dimensional graph showing the effects of two independent variables on performance.