Name
Abstract | ||
|---|---|---|
Nowadays, most companies and organizations rely on computer systems to run their work processes. Therefore, the analysis of how these systems are used can be an important source of information to improve these work processes. In the era of Big Data, this is perfectly feasible with current state-of-art data analysis tools. Nevertheless, these data analysis tools cannot be used by general users, as they require a deep and sound knowledge of the algorithms and techniques they implement. In other areas of computer science, domain-specific languages have been created to abstract users from low level details of complex technologies. Therefore, we believe the same solution could be applied for data analysis tools. This article explores this hypothesis by creating a Domain-Specific Language (DSL) for the educational domain. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-27653-3_8 | Communications in Computer and Information Science |
Keywords | Field | DocType |
Domain-specific languages,Big data,Educational data mining | Domain-specific language,Analysis tools,Data science,World Wide Web,Digital subscriber line,Computer science,Big data,Educational data mining | Conference |
Volume | ISSN | Citations |
563 | 1865-0929 | 2 |
PageRank | References | Authors |
0.38 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alfonso de la Vega | 1 | 3 | 3.76 |
| Diego García-Saiz | 2 | 57 | 10.32 |
| Marta E. Zorrilla | 3 | 51 | 16.05 |
| Pablo Sánchez | 4 | 50 | 12.01 |