A double-index-based k-dominant skyline algorithm for incomplete data stream

Since the multi-criteria decision support applications is playing an important role, skyline query in the field of data mining has been an important research field in recent years. But with the increase of the dimension, mutual domination of data becomes weaker. The existing k-dominant skyline algorithms need to be improved in the efficiency of time and space complexity. We propose a double-index-based k-dominant skyline algorithm for incomplete data stream. Experimental evidence shows that the proposed algorithm is superior to other similar algorithms in efficiency and performance.