Your browser does not allow JavaScript!
JavaScript is necessary for the proper functioning of this website. Please enable JavaScript or use a modern browser.
Open Science Slovenia
Open Science
DiKUL
slv
|
eng
Search
Browse
New in RUL
About RUL
In numbers
Help
Sign in
Perspectives of data mining in improving data collection processes in official statistics
ID
Hudec, Miroslav
(
Author
),
ID
Juriová, Jana
(
Author
)
URL - Presentation file, Visit
http://www.stat-d.si/mz/mz10.1/Hudec2013.pdf
Image galllery
Abstract
Statistical offices are crucial institutions for collecting data about various aspects of society. Nevertheless, data collection copes with nonresponse in surveys and problem of missing values. Therefore, efforts focused on increasing response rates and the estimation of missing values are topics which need continual improvement. The paper examines advantages of soft computing techniques on small-scale case studies related to reminder letters, respondents classification and estimation of missing values. Fuzzy sets have membership degree valued in the [0, 1] interval which implies that similar entities could be similarly treated in reminders and with some restriction in imputation. Neural networks are suitable when the borders of classes are not easily definable and databases contain incomplete records. In such a case the neural network can identify the most similar class for each entity and this enables the imputation of missing values. Finally, the paper discusses an efficient way for design and implementation of tools in the cooperation among statistical institutes.
Language:
English
Keywords:
podatkovne baze
,
statistika
Work type:
Not categorized
Organization:
FDV - Faculty of Social Sciences
Year:
2013
Number of pages:
Str. 65-81
Numbering:
Vol. 10, no. 2
PID:
20.500.12556/RUL-74894
ISSN:
1854-0023
UDC:
311:004.8
COBISS.SI-ID:
32493405
Publication date in RUL:
21.12.2015
Views:
607
Downloads:
98
Metadata:
Cite this work
Plain text
BibTeX
EndNote XML
EndNote/Refer
RIS
ABNT
ACM Ref
AMA
APA
Chicago 17th Author-Date
Harvard
IEEE
ISO 690
MLA
Vancouver
:
Copy citation
Share:
Similar documents
Similar works from RUL:
Similar works from other Slovenian collections:
Back