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Titlebook: Indirect Questioning in Sample Surveys; Arijit Chaudhuri,Tasos C. Christofides Book 2013 Springer-Verlag Berlin Heidelberg 2013 62D05, 62P

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书目名称Indirect Questioning in Sample Surveys
编辑Arijit Chaudhuri,Tasos C. Christofides
视频videohttp://file.papertrans.cn/464/463691/463691.mp4
概述Collects recent as well as the most important techniques in the modern field of indirect questioning.Includes the issue of the protecting privacy, which is crucial in surveys of human populations.Is s
图书封面Titlebook: Indirect Questioning in Sample Surveys;  Arijit Chaudhuri,Tasos C. Christofides Book 2013 Springer-Verlag Berlin Heidelberg 2013 62D05, 62P
描述.Indirect questioning is a crucial topic in surveys of human populations. When the issue is about a stigmatizing characteristic (for example about illegal drug use), standard survey methodologies are destined to fail because, as expected, people are not willing to reveal incriminating information or information violating their privacy.  Indirect questioning techniques have been devised so that the privacy of participants in a sample survey is protected and at the same time good estimates of certain parameters (e.g. the percentage of people in a certain community who use illegal drugs) can be delivered. The topic is modern and still under development..Indirect Questioning in Sample Surveys. represents a collection of the most important and recent techniques of indirect questioning, including various versions of randomized response, the item count technique, the nominative technique, the three-card method, non-randomized response models and negative surveys, while also exploring the key aspect of protecting privacy..
出版日期Book 2013
关键词62D05, 62P25; indirect questioning; protection of privacy; randomized response; sampling design; survey m
版次1
doihttps://doi.org/10.1007/978-3-642-36276-7
isbn_softcover978-3-662-51255-5
isbn_ebook978-3-642-36276-7
copyrightSpringer-Verlag Berlin Heidelberg 2013
The information of publication is updating

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Arijit Chaudhuri,Tasos C. Christofidesan be arranged in machine-readable formats, useful for several applications that need structured semantic knowledge. The work presented in this paper explores different strategies to automate the extraction of semantic relations from texts in Portuguese, Galician and Spanish. Both machine learning (
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