Data mining II:
Saved in:
| Format: | Book |
|---|---|
| Language: | English |
| Published: |
Southampton [u.a.]
WIT Press
2000
|
| Series: | Management information systems
2 |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | 628 S. graph. Darst. |
| ISBN: | 185312821X |
Staff View
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| 300 | |a 628 S. |b graph. Darst. | ||
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Record in the Search Index
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| adam_text |
Contents
Section
1: Applications
of Data
Mining in Science,
Engineering, Business,
Industry and Medicine
Web
mining through the
online
analyst
A. Zanosi
.
З
Bayesian networks for knowledge discovery in a database from
the program for genetic improvement of the Nelore breed
S.O.
Rezende,
CAJ.
da Rocha
&
R.B.
Lobo
. 15
Using a data mining workbench for micro and macro
economic modelling
D.F. Nettleton,
V.L.
Fondino,
M.
Witty
&
E. Vilajosana
.25
Small business modeling within the financial accounting
conceptual framework
A.B.
Thornton— Trump
&
W.
Fu
.35
Paperwork reduction by means of data mining
A. Pagnoni, S.
Parisi
&
D.
Attorrese
.45
CRM
in a real-world insurance company
G. Pedrazzi, R.
Turra
&
A. Zanasi
.53
A data-mining alternative to model hospital operations:
clinical costs and predictions
D.
Riaño
&
S.
Prado
.63
Optimal entrocopy encoders for mining multiply resolved data
R.A. DeVore, LS. Johnson,
С
Pan
&
R.C. Sharpley
.73
Acquisition of KANSEI based on fuzzy inference and
m u
Iti vantate
analysis
T. Fukuda,
T. Chikazawa, Y. Hasegawa, F. Kobayashi,
K. Shimojima
&
Y. Yamaguchi
.83
Data
mining for database
marketing
at
Garanti Bank
O.F.
Alis,
E.
Karakurt
&
P. Melli
.93
Use of equation discovery: Oscillating flow in a U-tube
G.
Petkovšek&B. Kompare
. 109
The use of learning classifier systems in the direct marketing industry
A. Greenyer
. 119
Section
2:
Data Warehousing and Databases
KR and model discovery from active
DB
with predictive logic
CF.
Nourani
&
G.S.L Loo
. 131
Metadata
-
based data auditing
H. Hinrichs&T. Wiïkens
. 141
An analysis of the integration between data mining applications
and database systems
E.
Bezerra,
M.
Mattoso &
G. Xexéo
. 151
Design
of a data warehouse to
support
the
management
of
academic institutions
L.
Marín,
M. Hassan, A.
Lozano,
G. Manassero
&
O.
Chiotti
. 161
Section
3:
Internet Applications
Automatic construction
of ontology from text databases
N.
Zhong, Y.Y. Yao& Y. Kakemoto
. 173
Attractability: an indicator for optimising the design of a web site
A. Platis, P. Tselios& G. Vouros
. 181
Section
4:
Data Mining Methodologies
A new algorithm for finding association rules
L. Dumitriu, C. Tudorie, E. Pecheanu
&
A.
Istrate. 195
Local feature selection for heterogeneous problems
/.
Skrypnyk, A. TsymbalSc S. Puuronen
.203
Content in context: a data-driven approach
J. Vernau
. 213
Section
5:
Knowledge
Discovery and Data
Mining
An architecture
for ABEN-KDD- an agent-based environment for
knowledge discovery in databases
M.
Sousa,
M. Gottgtroy,
N. Ebecken&
Μ.
Rodrigues
.221
Discovering graph structures in high dimensional spaces
V.
Dubois
&
M
Quafafou
.231
Discovering salient data features by composing and manipulating
logical equations
D.E.
Sitnikov, B. D'Cruz&P.E. Sitnikova
.241
A qualitative spatial reasoning approach in knowledge discovery
in spatial databases
M
Santos
&
L.
Amaral
.249
A fuzzy
-
based conceptual KDD approach: the SaintEtiQ system
G.
Raschia
&N. Mouaddib
.259
Supervised knowledge discovery from incomplete data
A. Kalousis
&
M.
Hilario
.269
Data scale reduction via instances summarization using
the Rough Set Theory
G. Gaunter
&
M. Quafafou
.279
Data mining in temporal sequences: a technique based on
MC
S.
Massa
&
P.P. Puliafito
.289
Data mining telecommunications network data for fault management
and development testing
R.
Sterriti,
K. Adamson,
CM.
Shapcott
&
Е.Р.
Curran
.299
Higher order mining: modelling and mining the results of
knowledge discovery
M. Spiliopoulou
&
J.F. Roddick
.309
A computational environment for extracting rules from databases
J.A. Baranauskas, M.C Monard
&
G.E.A.P.A. Batista
.321
Considerations about the effectiveness of inductive learning process
in data-mining context
F. Souza&M. Gottgtroy
.331
Section
6:
Neural Networks and Decision Trees
The deterministic evolutionary learning algorithm
R. Tsaih
.343
Wrapped feature selection for binary classification Bayesian
régularisation
neural networks: a database marketing application
5.
Viaene, B. Baesens, D. Van
den Poel,
G. Dedené,
J. Vandenbulcke
&
J. Vanthienen
.353
Web
text mining using
a hybrid
intelligent system based on KDT,
expert system and neural network
F.H. Fukuda, E.L.P.
Passos,
M.A.
Pacheco,
LB.
Neto, J.
Valerio,
V.
De Roberto
Junior,
E.R. Antonio
&
L. Chiganer
.363
Alleviating the complexity of the Combinatorial Neural Model using a
committee machine
H. A. do
Prado,
K.F.
Machado
&
P.M.
Engel.373
Application of decision tree classifiers to computer intrusion detection
N.
Ye
&
X.Li
.381
Effects of attribute selection measures and sampling policies on
functional structures of decision trees
H. Du, S.
Jassim
&
M.F.
Obatusin.391
Section
7:
Genetic Algorithms and Parallel Techniques
Credit approval by a clustering genetic algorithm
E.R. Hruschka
&
N.F.F. Ebecken
.403
Designing optimized pattern recognition systems by learning
Voronoi vectors using genetic algorithms
C.M.N.A.
Pereira
&
R. Schirru
.413
Scalable parallel algorithms for predictive modelling
P. Christen, M. Hegland, O. Nielsen, S. Roberts
&
I. Altas
.423
Section
8:
Visualisation in Data Mining
Interactive
rale-network layout with a genetic algorithm in a
knowledge discovery process
P. Kuntz, R.
Lehn &
H. Briand
.435
Visualisation for Data Mining telecommunications network data
R.
Sterriti,
E.P.
Curran,
K. Adamson
&
CM.
Shapcott.
.445
InfoZoom
-
Analysing Formula One racing results with an interactive
data mining and visualisation tool
M. Spenke&C. Beilken
.455
Section
9:
Clustering and Classification Techniques
Evolving TSK fuzzy rules for classification tasks by Genetic Algorithms
R.P.
Espíndola
&
N.F.F. Ebecken
.467
Hierachical clustering for data mining by RBF network
Ö.
Ciftcioglu
&
S. Sariyildiz
.477
Detecting visual feature importance via tree classifiers. An experience
С
Brambilla,
I.
Gagliardi,
R.
Schettini
&
A. Valsasna
.487
Input
dependent misclassification costs for cost-sensitive classifiers
J. Hollmén,
M. Skubacz&M. Taniguchi
.495
Undirect
knowledge discovery by using singular value decomposition
E.
Maltseva,
С.
Pizzuti
&
D.
Talia
.505
A clustering algorithm using the tabu search approach with
simulated annealing
S
-С.
Chu
&
J.F.
Roddick
.515
Cluster generation using tabu search based maximum descent algorithm
J.S. Pan, S.C.
Chu
&
Z.M.
Lu
.525
Stabilization of regression trees
T. Urbana T. Kämpke
.
535
Influence
of lossy compression on hyperspectral image
classification accuracy
J.
Mìnguillón,
J.
Pujol,
J.
Serra
&
I. Ortuño
.545
Section
10:
Tools for Pattern Discovery
Modeling dynamical systems by recurrent neural networks
H.G.
Zimmermann &
R.
Neuneier.557
A visual data mining tool to support cooperative learning
J.G.
le Roux
&
H.L. Viktor
.567
A new insight into the algebraic structure of the exponential smoothing
algorithm of Brown
A. Bellacicco
.577
Section
11:
Case Studies
A case based reasoning framework to extract knowledge from data
F.
Rodrigues,
С.
Ramosa
P. Henriques
.589
Mining customer preference ratings for product recommendation
using the support vector machine and the latent class model
W.K. Cheung, J.T. Kwok, M.H. Law&K-C. Tsui
.601
Data mining a large health insurance database
A.F. Gualtierotti
.611
Case study of a retail bank marketing datamart development
A. Cathie
.619
Index of Authors
629 |
| any_adam_object | 1 |
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| discipline | Informatik Wirtschaftswissenschaften |
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| spelling | Data mining II ed.: N. Ebecken ... Southampton [u.a.] WIT Press 2000 628 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Management information systems 2 Data Mining - Congrès Data mining gtt Data warehouse gtt Data mining Congresses Data Mining (DE-588)4428654-5 gnd rswk-swf (DE-588)1071861417 Konferenzschrift 2000 Cambridge gnd-content Data Mining (DE-588)4428654-5 s DE-604 Ebecken, N. Sonstige oth Management information systems 2 (DE-604)BV013392289 2 Digitalisierung TU Muenchen application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009135828&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
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| title | Data mining II |
| title_auth | Data mining II |
| title_exact_search | Data mining II |
| title_full | Data mining II ed.: N. Ebecken ... |
| title_fullStr | Data mining II ed.: N. Ebecken ... |
| title_full_unstemmed | Data mining II ed.: N. Ebecken ... |
| title_short | Data mining II |
| title_sort | data mining ii |
| topic | Data Mining - Congrès Data mining gtt Data warehouse gtt Data mining Congresses Data Mining (DE-588)4428654-5 gnd |
| topic_facet | Data Mining - Congrès Data mining Data warehouse Data mining Congresses Data Mining Konferenzschrift 2000 Cambridge |
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