| Summary: | Talent is the best group in human resources, and the Talents are the best group in human resources, and English-speaking talents are the most dynamic factor in productivity. In order to improve the quantitative analysis ability of the English talent aggregation effect, the English talents aggregation effect analysis model is proposed based on large-scale data collection technology. The collection information flow model of the hotspot big data of English talents aggregation effect is constructed. The high-dimensional feature grouping method is used to reconstruct the hotspot big data of the English talents aggregation effect. The piecewise linear test method is used to analyze the statistical characteristics of the hotspot big data of the English talents aggregation effect and extract the frequent vector set which reflects the hot big data category attribute of the English talents aggregation effect. According to the result of feature extraction, the fuzzy English talents aggregation is processed to realize the fusion of big data information of English talents aggregation effect hotspot. Combined with quantitative analysis method, the automatic classification of big data association rules is realized. The experimental and simulation results show that the proposed method is more accurate and effective than the traditional methods in collecting hotspot data, which is 26% and 76% higher than the traditional methods. This method has better accuracy and improved data aggregation effect in collecting hotspot data of English talents gathering and has strong collecting ability and characteristics. The research improved hotspot big data’s English talents gathering effect.
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