MINING OF TOP K DOMINATING QUERIES BASED ON PRIORITY OVER INCOMPLETE DATA
Sharanya Mohanan., Magniya Davis · Journal of Emerging Technologies and Innovative Research · 2018
Incompleteness of data is a serious issue and can have a significant effect on the conclusions that can be drawn from the data. Missing data can occur because of non response no information is provided for one or more items or whole unit. Incomplete data can also exists in wide spectrum of real datasets due to privacy preservation deice failure data loss and so on. In this paper for the first time we propose a method to handle incomplete data which consist of some missing dimensional values. Although some previous works are done but in this paper for the first time we introduce a new concept called priority value and this value is used to find top k dominating query over incomplete data[1]. The top k dominating query returns the K objects that dominates the maximum no of objects in a given dataset. Top K queries are also used for sliding window data streams[2].We formalize the problem and propose a skyline based algorithm to find top k objects in the result which dominates other objects based on dominance relationship