An algorithm based on time series similarity measurement for missing data filling

In data mining processing, filling incomplete data is very important in preprocessing of data mining project. An algorithm based on time series similarity measurement for incomplete data is proposed, this approach can fill missing data via following internal rule of data set reasonably. By experiments, we can draw a conclusion that algorithm is effective on condition that incomplete data are no more than half of the whole data in one case.