A semi-supervised crowdsourced labeling data integration method for label imbalance
A label imbalance and crowdsourcing labeling technology, which is applied in the field of label imbalance-oriented semi-supervised crowdsourcing labeling data integration, can solve problems such as label imbalance, different weights, and weight differences, and achieve the evaluation of weighted parameters Objective and accurate, accurate labeling results, and objective and accurate performance of ability assessment
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[0045] In order to describe the present invention more specifically, the technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.
[0046] The flow process of the inventive method is as figure 1 As shown, it specifically includes the following steps:
[0047] Step (1): The evaluation of weighted parameters is obtained from the set of correct results and the corresponding crowdsourced annotation results Find the weighted parameter set {w j |j∈[1,C]} (that is, W), where is the correct label for the mth object in the correct result, Indicates the number of times the kth worker marked the result as j on the mth object, which is the training set corresponding to the correct result, w j Indicates the weight corresponding to the jth tag, M is the total number of objects, C is the number of tag types, and K is the total number of taggers. The method is introduced below, and the step...
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