The task of similarity search in multimedia databases is usually accomplished by range or k nearest neighbor queries. However, the expressing power of these “single-example” queries fails when the user’s delicate query intent is not available as a single example. Recently, the well-known skyline operator was reused in metric similarity search as a “multi-example” query type. When applied on a m...

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...

With rapid increase of the number of applications as well as the sizes of data, multi-query processing on the MapReduce framework has gained much attention. Meanwhile, there have been much interest in skyline query processing due to its power of multi-criteria decision making and analysis. Recently, there have been attempts to optimize multi-query processing in MapReduce. However, they are not ...

In the last decade, skyline queries have been extensively studied for different domains because of their wide applications in multi-criteria decision making and search space pruning. A skyline query returns all the interesting points in a multi-dimensional data set that are not dominated by any other point with respect to all dimensions. However, real world data sets are seldom complete, i.e. d...

In recent years much attention has been focused on evaluating skylines, however the existing techniques primarily focus on skyline algorithms over single sets. These techniques face two serious limitations, namely (1) they define skylines to work on a single set only, and (2), they treat skylines as an “add-on”, loosely integrated on top of the query plan. In this work, we investigate the evalu...

Current skyline evaluation techniques follow a common paradigm that eliminates data elements from skyline consideration by finding other elements in the dataset that dominate them. The performance of such techniques is heavily influenced by the underlying data distribution (i.e. whether the dataset attributes are correlated, independent, or anti-correlated). In this paper, we propose the Lattic...

Recent studies have linked demographic changes and epidemiological patterns in bacterial populations using coalescent-based approaches. We identified 26 studies using skyline plots and found that 21 inferred overall population expansion. This surprising result led us to analyze the impact of natural selection, recombination (gene conversion), and sampling biases on demographic inference using s...

Panorama is a web application for storing, sharing, analyzing, and reusing targeted assays created and refined with Skyline,1 an increasingly popular Windows client software tool for targeted proteomics experiments. Panorama allows laboratories to store and organize curated results contained in Skyline documents with fine-grained permissions, which facilitates distributed collaboration and secu...

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...

Uncertain data are inherent in some important applications. Although a considerable amount of research has been dedicated to modeling uncertain data and answering some types of queries on uncertain data, how to conduct advanced analysis on uncertain data remains an open problem at large. In this paper, we tackle the problem of skyline analysis on uncertain data. We propose a novel probabilistic...