Abstract:

Cloud computing provides the platform for the associate rule mining and query of big data. Data often contains artificially added uncertainty to prevent the information disclosure. How to allow users to query the result of association rules mining from uncertain data transparently is an urgent problem to be solved in the query of big data mining results. The uncertain big data for sharing achieves uniform distributed characteristic through generalizing precise data, this characteristic is not conductive to accurate queries but can offer convenience for the query on association rules mining result set. Firstly, the association rule library is built by UFIDM algorithm and the Rtree indexes are constructed for both generalized identifiers and sensitive attributes separately in order to improve the query efficiency. Secondly, the generalization value granularity transform method and UARS query algorithm are proposed on this basis. Finally, theoretical analysis and experimental results demonstrate the feasibility and effectiveness of the algorithm.

Key words: big data;uniform distributed uncertain data;association rules;granularity transform query