4. Processing During this stage, the data inputted to the computer in the previous stage is actually processed for interpretation. Processing is done usingmachine learningalgorithms, though the process itself ma
读《A Comparision of Join Algorithms for Log Processing in MapReduce》 这周组会我讲了《A Comparision of Join Algorithms for Log Processing in MapReduce》这篇文章,是2010年发在ACM SIGMOD国际数据管理会议上的,就是设计了一些数据的连接算法,然后为每种算法作了不同的预处理,测试性能,最后还测试了一...
For example, digital assistants such as Microsoft's Cortana often use complex machine learning algorithms for speech recognition and for understanding user queries. Incoming user queries can be considered to be a stream that needs to be responded to in low latency. However, over time the historic...
Within the context of modern data analytics, much of the data processing lifecycle is automated using sophisticated hardware and algorithms. Often, this is the precursor to more in-depth and hands-on data analysis, where the information gleaned is further analyzed to extract more focused and actio...
However, due to the multiplexed fragment ion spectra, DIA requires more elaborate data processing algorithms and software solutions for spectral deconvolution, which typically make use of pre-recorded spectral libraries. Moreover, apart from the unambiguous identification of the phosphopeptide sequence, ...
It is increasingly used in edge-embedded devices to accelerate the inference process of remote sensing data processing algorithms. González et al. [8] proposed an algorithm based on FPGA for automatically detecting targets to address the challenge of poor instantaneity of target detection in ...
uses machine learning algorithms to automate data cleaning tasks. it provides a visual interface for exploring and cleaning data and tools for transforming and reshaping it. talend data preparation - a cloud-based tool that provides a wide range of features for cleaning and transforming data, ...
[17]. Previously, we described how to handle bursty streams by switching stream processing algorithms in a distributed environment[18]. In this work, we particularly focused on minimizing the switching time, i.e., the response time of the adaptation. This sparked our interest in obtaining an ...
This usually involves applying statistical ormachine learning techniques. It uses special algorithms and statistical calculations, and enterprises can use software suites like SAS for this. Reporting: This is the final step in processing, and it involves presenting the findings of the analysis to write...
Tensor computation leads to a heavy computational burden in some cases. Therefore, high-performance tensor computation algorithms and efficient software are called for. • Apart from the data processing community, tensors are intensively investigated in physics as well. It is quite important to make...