What does big data mining technology involve?

The main contents of big data mining technology include pattern tracking, data cleaning and preparation, data mining technology based on classification, outlier detection, association and clustering.

Based on the characteristics of data in macro environment, mining technology and its correspondence;

1. There are many data sources, and the research object of big data mining often involves not only one business system, but also the fusion analysis of multiple systems. Therefore, powerful ETL technology is needed to integrate the data of multiple systems, which may have different standards and need to be cleaned.

2. The dimensions of data are very high, and the integrated data are not only those of traditional data mining, but also hundreds of dimensions, which requires dimension reduction technology.

3. The calculation of a large number of data cannot be calculated on a single server, and distributed calculation is needed. Therefore, to master various distributed computing frameworks, such as hadoop and spark, it is necessary to master the distributed implementation of machine learning algorithms.

Data mining: the existing data mining and machine learning technologies need to be improved; Develop new data mining technologies such as data network mining, special group mining and graph mining; Break through data fusion technologies such as object-based data connection and similarity connection; Break through domain-oriented big data mining technologies such as user interest analysis, network behavior analysis and emotional semantic analysis.

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