关键词: 众包, 模式匹配, 熵, Beta分布

Abstract: Schema matching is a fundamental problem in data management. With the growing of data sets, using automated schema matching tool can greatly save matching time. However, the results of automated matching tools often have uncertainty, and this uncertainty is difficult to eliminate. This paper puts forward a strategy for publishing questions in schema matching via crowdsourcing: Entropy-Beta. This strategy optimizes the process of publishing in the phase of publishing questions, and this operate can improve the efficiency of pattern matching to resolve uncertainty. On this basis, this strategy provides a method to evaluate the answer accuracy from crowdsourcing workers, and this method can improve the accuracy of solving the uncertainty of pattern matching efficiently. Finally, the experimental results show that “Entropy-Beta” strategy of publishing questions is more efficient. Moreover, under the fixed cost, the proposed strategy can improve the accuracy of problem solving.

Key words: crowdsourcing, schema matching, entropy, Beta distribution