کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
379091 659262 2008 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Privacy-preserving imputation of missing data
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Privacy-preserving imputation of missing data
چکیده انگلیسی

Handling missing data is a critical step to ensuring good results in data mining. Like most data mining algorithms, existing privacy-preserving data mining algorithms assume data is complete. In order to maintain privacy in the data mining process while cleaning data, privacy-preserving methods of data cleaning are required. In this paper, we address the problem of privacy-preserving data imputation of missing data. We present a privacy-preserving protocol for filling in missing values using a lazy decision-tree imputation algorithm for data that is horizontally partitioned between two parties. The participants of the protocol learn only the imputed values. The computed decision tree is not learned by either party.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Data & Knowledge Engineering - Volume 65, Issue 1, April 2008, Pages 40–56
نویسندگان
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