Name
Abstract | ||
|---|---|---|
We present an approach for forecasting labor demand in a services business. We introduce an arrangement of machine learning techniques, each constructed by necessity to overcome issues with data veracity and high dimensionality. |
Year | Venue | Keywords |
|---|---|---|
2017 | 2017 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | Machine Learning, Natural Language Processing, Workforce, Labor Economics, Forecasting |
Field | DocType | ISSN |
Fungibility,Labor demand,Computer science,Operations research,Curse of dimensionality,Artificial intelligence,Cluster analysis,Semantics,Machine learning | Conference | 2639-1589 |
Citations | PageRank | References |
2 | 0.39 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brian Johnston | 1 | 2 | 0.73 |
| Benjamin Zweig | 2 | 2 | 0.73 |
| Michael Peran | 3 | 5 | 2.17 |
| Charlie Wang | 4 | 2 | 0.39 |
| Rachel Rosenfeld | 5 | 2 | 0.73 |