Name
Abstract | ||
|---|---|---|
The SOFIA analytic recommender system helps non-expert users to select analytics (algorithms and their implementations) to fulfill a data mining task in an effective manner. The recommender is a novel framework that applies an ontology-driven approach to recommend a ranked list of analytics to fulfill a task based on the characteristics of the given dataset. SOFIA relies on an ontological representation of data science principles evolved by the data science community; it does not require training examples nor actual deployment of candidate analytics on given datasets. |
Year | Venue | Field |
|---|---|---|
2015 | International Semantic Web Conference (Posters & Demos) | Recommender system,Ontology,Data mining,Software deployment,Information retrieval,Ranking,Simulation,Computer science,Implementation,Analytics |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
2 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fatemeh Nargesian | 1 | 26 | 4.38 |
| Alain Biem | 2 | 288 | 18.64 |
| Prateek Jain 0001 | 3 | 0 | 0.34 |
| Srinivasan Parthasarathy | 4 | 4666 | 375.76 |
| Deepak S. Turaga | 5 | 564 | 48.11 |