Title :
SDM Techniques Based on TGSOM and its Application in R&D Performance Evaluation
Author :
Liu, Zhibin ; Hu, Hanxiang
Author_Institution :
Econ. & Manage. Dept., North China Electr. Power Univ., Baoding
Abstract :
Research and development activities (R&D) as the core competitiveness in the high-tech enterprises play an extremely important role and far-reaching significance. In order to measure the R&D performance of the high-tech enterprises scientifically and accurately, this paper introduces the tree-structured growing self-organizing maps (TGSOM) network into the spatial data mining (SDM) to be used in spatial clustering. This method not only can make up the limitation of the more data limit and biggish computation in the common spatial data mining, but also overcome the restriction of traditional maps (SOFM) that must appoint in advance. The performance measurement of 110 high-tech enterprises in Hebei Province shows that the results given by this method are reliable.
Keywords :
data mining; enterprise resource planning; performance evaluation; research and development management; self-organising feature maps; R&D performance evaluation; SDM techniques; TGSOM; biggish computation; core competitiveness; data limit; high-tech enterprises; research and development activity; spatial clustering; spatial data mining; tree-structured growing self-organizing maps; Data mining; Geoscience; Measurement; Neural networks; Relational databases; Research and development; Research and development management; Spatial databases; Statistical analysis; Transaction databases; R&D; SDM techniques; TGSOM; performance evaluation;
Conference_Titel :
Knowledge Discovery and Data Mining, 2009. WKDD 2009. Second International Workshop on
Conference_Location :
Moscow
Print_ISBN :
978-0-7695-3543-2
DOI :
10.1109/WKDD.2009.27
