Using multifactor-analysis to efficiently analyse large amounts of data in order to find a cluster of closely related projects for business opportunities, partnerships, competitor analysis and collaboration
This is your project among H2020.
8400+ projects currently funded
Source: European Commission
You’ve got a problem…
How will you ever find
projects effectively and
The 1-slide explanation
38 responses, scoring the
importance of NIST Cloud
characteristics for them selves
Out of these, your
collaboration opportunities lie
within this cluster!
(Had you provided your
A bit of statistics
Principal Component Analysis (Karl Pierson 1901, Harold Hotelling 1930)
Emphasises variance and patterns in data
Data transformation for dimension reduction in analysis
Hierarchical clustering using Euclidian distance
Form clusters of “similar” respondents, starting with 1-member
“Similarity” (i.e., distance) calculated using Euclidian distance function
Distance between clusters uses “weighed pair-group centroid”
performs well with large variance in cluster sizes
Yes you can.
But first, you must submit your scores!
SESA – 10 of 19 projects responded
ICEI – 4 of 13 projects responded
NATRES – 11 of 20 projects responded
DPSP – 3 of 24 projects responded