相关论文: An Efficient Skyline Computation Framework
Skyline queries are important in many application domains. In this paper, we propose a novel structure Skyline Diagram, which given a set of points, partitions the plane into a set of regions, referred to as skyline polyominos. All query…
With the advancement of technology, the data generated in our lives is getting faster and faster, and the amount of data that various applications need to process becomes extremely huge. Therefore, we need to put more effort into analyzing…
Multi-criteria decision analysis in databases has been actively studied, especially through the Skyline operator. Yet, few approaches offer a relevant comparison of Pareto optimal, or Skyline, points for high cardinality result sets. We…
Living in the Information Age allows almost everyone have access to a large amount of information and options to choose from in order to fulfill their needs. In many cases, the amount of information available and the rate of change may hide…
Advancements in tools like Shapely 2.0 and Triton can significantly improve the efficiency of spatial similarity computations by enabling faster and more scalable geometric operations. However, for extremely large datasets, these…
The skyline of a set $P$ of points ($SKY(P)$) consists of the "best" points with respect to minimization or maximization of the attribute values. A point $p$ dominates another point $q$ if $p$ is as good as $q$ in all dimensions and it is…
Bipartite graphs, modeling relationships between two types of entities, are widely used in practical applications. Community search, a fundamental problem in bipartite graphs, has gained significant attention. However, existing studies…
In this paper, for the first time, we introduce the concept of skyblocking, which aims to efficiently identify the "most preferred" blocking scheme in terms of a given set of selection criteria for entity resolution blocking. To capture all…
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…
Training a state-of-the-art deep neural network (DNN) is a computationally-expensive and time-consuming process, which incentivizes deep learning developers to debug their DNNs for computational performance. However, effectively performing…
Clustering is one of the major tasks in data mining. In the last few years, Clustering of spatial data has received a lot of research attention. Spatial databases are components of many advanced information systems like geographic…
The skyline concept has been introduced in order to exhibit the best objects according to all the criterion combinations and makes it possible to analyse the relationships between skyline objects. Like the data cube, the skycube is so…
Preparing high-quality datasets required by various data-driven AI and machine learning models has become a cornerstone task in data-driven analysis. Conventional data discovery methods typically integrate datasets towards a single…
Skyline queries are frequently used in data analytics and multi-criteria decision support applications to filter relevant information from big amounts of data. Apache Spark is a popular framework for processing big, distributed data. The…
Scientific endeavors such as large astronomical surveys generate databases on the terabyte scale. These, usually multidimensional databases must be visualized and mined in order to find interesting objects or to extract meaningful and…
Restricted skyline (rskyline) query is widely used in multi-criteria decision making. It generalizes the skyline query by additionally considering a set of personalized scoring functions F. Since uncertainty is inherent in datasets for…
A set of preferred records can be obtained from a large database in a multi-criteria setting using various computational methods which either depend on the concept of dominance or on the concept of utility or scoring function based on the…
{Multi-criteria decision analysis in databases has been actively studied, especially through the Skyline operator. Yet, few approaches offer a relevant comparison of Pareto optimal, or Skyline, points for high cardinality result sets. We…
The area of scientific research that deals with the simultaneous optimization of several (possibly conflicting) criteria is named multi-objective optimization. The ability to efficiently filter and extract interesting data out of large…
Given a graph, and a set of query vertices (subset of the vertices), the dynamic skyline query problem returns a subset of data vertices (other than query vertices) which are not dominated by other data vertices based on certain distance…