Abstract
The negative survey is an emerging method of collecting sensitive information. It could obtain the distribution of sensitive information while preserving the personal privacy. When collecting sensitive information, several questions are often provided together to the respondents. However, when reconstructing positive survey results of multiple questions, previous reconstruction methods have some shortcomings. In this paper, we propose a new reconstruction method for multi-question negative surveys. Experimental results show that our method could obtain more reasonable results.
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This work is partly supported by National Natural Science Foundation of China (No. 61175045).
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Jiang, H., Luo, W. (2018). Multi-question Negative Surveys. In: Tan, Y., Shi, Y., Tang, Q. (eds) Data Mining and Big Data. DMBD 2018. Lecture Notes in Computer Science(), vol 10943. Springer, Cham. https://doi.org/10.1007/978-3-319-93803-5_47
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DOI: https://doi.org/10.1007/978-3-319-93803-5_47
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