Name
Abstract | ||
|---|---|---|
In the era of big data, economic competitiveness is assured by decision making leveraging insights gained from large scale yet granular data sets from a rich diversity of areas. In this light, the METIS system collaboratively developed by a team at WPI, the Massachusetts High Tech Council and other institutions, emerges as an analytic platform offering dynamic modeling capabilities. The integrative data source is based on high fidelity cost and talent competitive metrics. METIS extracts, integrates and models rich economic, financial, educational and technological information from renowned public heterogeneous web data sources ranging from The US Census Bureau, The Bureau of Labor Statistics, to Institute of Education Sciences. The METIS technology creates a powerful tool that allows intuitive analysis of the key factors that drive Massachusetts cost and talent competitiveness relevant to high tech companies. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2630729.2630735 | DSMM |
Keywords | Field | DocType |
systemic risk,financial models,data | Financial modeling,Data source,Systemic risk,Metis,Knowledge management,Management,Index system,High tech,System dynamics,Engineering,Big data | Conference |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
12 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ramoza Ahsan | 1 | 6 | 3.53 |
| Rodica Neamtu | 2 | 9 | 4.26 |
| Jeff Stokes | 3 | 0 | 0.34 |
| Armend Hoxha | 4 | 0 | 0.34 |
| Jialiang Bao | 5 | 0 | 0.34 |
| Stefan Gvozdenovic | 6 | 1 | 2.71 |
| Ted Meyer | 7 | 0 | 0.34 |
| Nilesh Patel | 8 | 0 | 0.68 |
| Raghu Rangan | 9 | 0 | 0.34 |
| Yumou Wang | 10 | 0 | 0.34 |
| Dongyun Zhang | 11 | 0 | 0.68 |
| Elke A. Rundensteiner | 12 | 4076 | 700.65 |