Efficient subspace skyline query based on user preference using MapReduce

Efficient Parallel Spatial Skyline Evaluation Using MapReduce

This research presents an advanced MapReduce-based parallel solution to efficiently address spatial skyline queries on large datasets. In particular, given a set of data points and a set of query points, we first generate the convex hull of the query points in the first MapReduce phase. Then, we propose a novel concept called independent regions, for parallelizing the process of spatial skyline...

Efficient Selection of Various k-Objects for a Keyword Query Based on MapReduce Skyline Algorithm

Skyline View: Efficient Distributed Subspace Skyline Computation

Skyline queries have gained much attention as alternative query semantics with pros (e.g.low query formulation overhead) and cons (e.g.large control over result size). To overcome the cons, subspace skyline queries have been recently studied, where users iteratively specify relevant feature subspaces on search space. However, existing works mainly focuss on centralized databases. This paper aim...

Efficient Skyline Computation in MapReduce

Skyline queries are useful for finding interesting tuples from a large data set according to multiple criteria. The sizes of data sets are constantly increasing and the architecture of back-ends are switching from single-node environments to non-conventional paradigms like MapReduce. Despite the usefulness of skyline queries, existing works on skyline computation in MapReduce do not take full a...

User Feedback Based Query Refinement by Exploiting Skyline Operator

This paper presents FlexlQ, a framework for feedback based query refinement. In FlexiQ, feedback is used to discover the query intent of the user and skyline operator is used to confine the search space of the proposed query refinement algorithms. The feedback consists of both unexpected information currently present in the query output and expected information that is missing from the query ou...