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In a specified semantic context, the meaning of a vague concept is different from its literal meaning, which cannot meet the specified needs of the user. The focus of this paper is how to mine valuable implicit information by existing literal information in a specified context. In a specified context, the mass function is used to assign the basic label subset, and the label semantics framework is used to compute the appropriate degree of the corresponding logical expressions of a vague concept in the specified context. At the same time, in order to demonstrate the effectiveness of this method, implicit information mining is carried out on the company size, profession and position on the collaborative ability platform of the Chamber of commerce. The combination of three factors, appropriate degree of different individuals is computed in a specified semantic context. The experimental results show that the proposed method can effectively mine the implicit information in the specified context, which is more consistent with the actual situation.
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