Output details
11 - Computer Science and Informatics
University of Stirling
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Article title
A Neural Network-based Framework for the Reconstruction of Incomplete Data Sets
Type
D - Journal article
Title of journal
Neurocomputing
Article number
-
Volume number
73
Issue number
16
First page of article
3039
ISSN of journal
0925-2312
Year of publication
2010
URL
-
Number of additional authors
1
Additional information
<13> Large high-dimensional datasets are frequently incomplete, causing issues for most analysis algorithms. The algorithm presented in this paper outperforms the existing algorithms, enabling more effective analysis of large incomplete datasets. It has been used as a comparator by a number of other studies, for example, X. Zhang, Xunan, Cognitive Computation, June 2013; L. Hung-Chin, Neurocomputing, April 2013.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
9
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
