Fuzzy keyword search over probabilistic XML data

The uncertainty and imprecision are intrinsic in data collected in various applications. This paper proposes an approach to compute results probabilities without generating possible worlds after defining fuzzy keyword search semantics in terms of possible world semantics. Meanwhile, we allow approximate matching between input keywords and the strings in the underlying data, even the input keywords contains spelling minor errors. We propose efficient algorithms, and effective ranking functions to facilitate fuzzy keyword search over probabilistic XML data. This paper propose a probability threshold based fuzzy keyword search method to efficiently identify results. The extensive experimental results shows that our proposed method is an effective way to solve the problem of fuzzy keyword search over probabilistic XML data, and it could significantly reduce the execution time and achieves both high result quality and search efficiency.