Contribution of big data in E-leaming. A methodology to process academic data from heterogeneous sources.
Gladys Alicia Tenesaca LunaJanneth ChicaizaMaria Belen Mora ArciniegasJuan Pablo Urena TorresVeronica Alexandra Segarra FaggioniMarlon Santiago Viñán-LudeñaPublished in: SCCC (2016)
Keyphrases
- big data
- heterogeneous sources
- massive data
- data analysis
- data processing
- data sets
- data sources
- high volume
- database
- machine learning
- business intelligence
- vast amounts of data
- massive datasets
- cloud computing
- knowledge discovery
- multiple sources
- statistical learning
- unstructured data
- information sources
- query language
- feature space
- data science