Big Data Mining Algorithm Based on Semantic Segmentation on Heterogeneous Multi-Core Platforms

In order to improve the ability of accurate big data mining with multi-core heterogeneous boards, a semantic segmentation-based method for accurate big data mining with multi-core heterogeneous boards is proposed. The fuzzy information detection model proposed in this paper for constructing big data with multi-core heterogeneous boards based on semantic segmentation improves the feature matching model of data mining by nearly 7%. Construct a feature matching output model for big data with multi-core heterogeneous boards, and use semantic segmentation algorithm extraction methods for feature extraction and statistical analysis of big data with multi-core heterogeneous boards. Establish a semantic dynamic feature analysis model for big data on a heterogeneous multi-core platform, and extract statistical features of big data on a heterogeneous multi-core platform.