Cross-Domain Data Processing Based on Computer Technology and Big Data

Cross-Domain Data Processing Based on Computer Technology and Big Data

연구 분야: Databases

학회: International Conference on Innovative Computing

As computer technology develops rapidly and the era of big data arrives, a large amount of data resources have been generated in various fields. Traditional data processing methods are usually limited to a single field and have difficulty in handling the complexity and diversity of cross-domain data. The standard deviation measurement algorithm is utilized to assess data dispersion and recognize key fluctuation features. Big data mining algorithms are utilized for deep feature extraction to mine implicit patterns and association rules. Therefore, this paper combines the standard deviation measurement algorithm with big data mining technology for comprehensive data preprocessing. Finally, the preprocessed data are combined with the extracted features to build a classification model to realize precise analysis and decision support for cross-domain data. Experiments demonstrate that the method in this paper can significantly improve the efficiency and accuracy of cross-domain data processing. The findings indicate that the method in this paper performs well in processing cross-domain data. The data processing speed is in the range of −0.05 mps to 2.00 mps, with a mean of 1.14 mps.