Sentence examples for approaches data from inspiring English sources
Compared with traditional approaches, data mining in data streams is more challenging since several extra requirements need to be satisfied.
In depth-based approaches, data objects are organized in layers in the data space, with the expectation that shallow layers are more likely to contain outlying data objects than the deep layers [25].
For the evaluation process to be used in dynamic traffic flow control approaches, data collection points are positioned at the 50th meter of the downstream link as proposed in [14].
The malware detection approaches were compared and analyzed according to various essential factors such as classification approaches, data analysis methods, the number of the used dataset, accuracy factor and case study analysis.
Work [24] conducts an empirical comparison of three computing diagrams for large graph processing, which are RDBMS-like approaches, data parallel approach (e.g. Pregel) and in-memory graph exploration approach.
Starting from the biological sample of interest and sequencing by different approaches data can be processed by assembly into contigs/scaffolds or directly undergo prediction analyses and/or comparison with reference databases.
This can in principle be achieved by two approaches, data-driven as in [7] or model-driven as in [5].
In particular, we present two approaches: data-domain and functional, which differ in the way that the decomposition of the application is performed.
Comparing to traditional well-log based brittleness approaches, data-based approaches show its wider applications because the integration of mineralogical composition and well log information can provide continuous brittleness profile in terms of high accuracy while acoustic full waveform velocities are no longer necessary inputs in brittleness evaluation.
In contrast to the previous two approaches, data-mining approaches are preferred for detecting high dimensional interactions.
Current strategies for biomarker discovery tend to focus on one of two approaches: data-driven [ 5] or expert knowledge-driven [ 6].
