Name
Abstract | ||
|---|---|---|
Linked Stream Data, i.e., the RDF data model extended for representing stream data generated from sensors social network applications, is gaining popularity. This has motivated considerable work on developing corresponding data models associated with processing engines. However, current implemented engines have not been thoroughly evaluated to assess their capabilities. For reasonable systematic evaluations, in this work we propose a novel, customizable evaluation framework and a corresponding methodology for realistic data generation, system testing, and result analysis. Based on this evaluation environment, extensive experiments have been conducted in order to compare the state-of-the-art LSD engines wrt. qualitative and quantitative properties, taking into account the underlying principles of stream processing. Consequently, we provide a detailed analysis of the experimental outcomes that reveal useful findings for improving current and future engines. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-35173-0_20 | International Semantic Web Conference |
Keywords | Field | DocType |
detailed analysis,corresponding methodology,state-of-the-art lsd engines wrt,rdf data model,linked stream data,corresponding data model,stream data,considerable work,evaluation environment,realistic data generation,customizable evaluation framework | Data mining,Data modeling,Social network,Computer science,System testing,Popularity,Stream processing,Data model,Database,Test data generation,RDF | Conference |
Citations | PageRank | References |
44 | 1.39 | 21 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Danh Le Phuoc | 1 | 648 | 31.01 |
| Minh Dao-Tran | 2 | 395 | 20.39 |
| Minh-Duc Pham | 3 | 220 | 10.55 |
| Peter Boncz | 4 | 2517 | 244.81 |
| Thomas Eiter | 5 | 7238 | 532.10 |
| Michael Fink | 6 | 1145 | 62.43 |