Research on Word Vector Training Method Based on Improved Skip-Gram Algorithm

Table 1

Performance of each model on semantic relevance tasks (X100).

Model	Wordsim-24	Wordsim-29
	44.01	53.33
SEING	42.88	49.81
Skip gram	43.61	52.59
Proposed	46.89	54.78