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A multi-attribute, multi-weight clustering approach to managing e-mail overload

Author
SCHUFF, David1 ; TURETKEN, Ozgur1 ; D'ARCY, John2
[1] Fox School of Business and Management, Temple University, 1810 N 13th Street, Philadelphia, PA 19122, United States
[2] Department of Computer and Information Sciences, Towson University, 8000 York Road, Towson, MD 21252, United States
Source

Decision support systems. 2006, Vol 42, Num 3, pp 1350-1365, 16 p ; ref : 49 ref

ISSN
0167-9236
Scientific domain
Electronics; Computer science
Publisher
Elsevier Science, Amsterdam
Publication country
Netherlands
Document type
Article
Language
English
Author keyword
Clustering Electronic mail Empirical study Information overload
Keyword (fr)
Analyse amas Classification hiérarchique Classification non supervisée Courriel Fouille donnée Méthode empirique Surcharge
Keyword (en)
Cluster analysis Hierarchical classification Unsupervised classification Electronic mail Data mining Empirical method Overload
Keyword (es)
Analisis cluster Clasificación jerarquizada Clasificación no supervisada Correo electrónico Busca dato Método empírico Sobrecarga
Classification
Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02B Software / 001D02B07 Memory organisation. Data processing / 001D02B07B Data processing. List processing. Character string processing

Discipline
Computer science : theoretical automation and systems
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
18390608

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

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