Dimitris Papadias

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Antomn Guttman100
Timos K. Sellis100
Christos Faloutsos98
Nick Roussopoulos87
Yannis Theodoridis78
135Yannis Manolopoulos
110Nikos Mamoulis
99Yufei Tao
86Alexandros Nanopoulos
84Apostolos N. Papadopoulos

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1992
2016
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Progressive skyline computation in database systems
The skyline of a <i>d</i>-dimensional dataset contains the points that are not dominated by any other point on all dimensions. Skyline computation has recently received considerable attention in the database community, especially for progressive methods that can quickly return the initial results without reading the entire database. All the existing… (More)
Query Processing in Spatial Network Databases
Despite the importance of spatial networks in real-life applications, most of the spatial database literature focuses on Euclidean spaces. In this paper we propose an architecture that integrates network and Euclidean information, capturing pragmatic constraints. Based on this architecture, we develop a Euclidean restriction and a network expansion… (More)
An Optimal and Progressive Algorithm for Skyline Queries
The skyline of a set of <i>d</i>-dimensional points contains the points that are not dominated by any other point on all dimensions. Skyline computation has recently received considerable attention in the database community, especially for progressive (or online) algorithms that can quickly return the first skyline points without having to read the entire… (More)
Preventing Location-Based Identity Inference in Anonymous Spatial Queries
The increasing trend of embedding positioning capabilities (for example, GPS) in mobile devices facilitates the widespread use of location-based services. For such applications to succeed, privacy and confidentiality are essential. Existing privacy-enhancing techniques rely on encryption to safeguard communication channels, and on pseudonyms to protect user… (More)
Conceptual Partitioning: An Efficient Method for Continuous Nearest Neighbor Monitoring
Given a set of objects <i>P</i> and a query point <i>q,</i> a <i>k</i> nearest neighbor (<i>k</i>-NN) query retrieves the <i>k</i> objects in <i>P</i> that lie closest to <i>q.</i> Even though the problem is well-studied for static datasets, the traditional methods do not extend to highly dynamic environments where multiple continuous queries require… (More)
Reverse kNN Search in Arbitrary Dimensionality
Given a point q, a reverse k nearest neighbor (RkNN) query retrieves all the data points that have q as one of their k nearest neighbors. Existing methods for processing such queries have at least one of the following deficiencies: (i) they do not support arbitrary values of k (ii) they cannot deal efficiently with database updates, (iii) they are… (More)
MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries
Among the various types of spatio-temporal queries, the most common ones involve window queries in time. In particular, timestamp (or timeslice) queries retrieve all objects that intersect a window at a specific timestamp. Interval queries include multiple (usually consecutive) timestamps. Although several indexes have been developed for either type,… (More)
Continuous monitoring of top-k queries over sliding windows
Given a dataset <i>P</i> and a preference function <i>f</i>, a top-k query retrieves the <i>k</i> tuples in <i>P</i> with the highest scores according to <i>f</i>. Even though the problem is well-studied in conventional databases, the existing methods are inapplicable to highly dynamic environments involving numerous long-running queries. This paper studies… (More)
The TPR*-Tree: An Optimized Spatio-Temporal Access Method for Predictive Queries
A predictive spatio-temporal query retrieves the set of moving objects that will intersect a query window during a future time interval. Currently, the only access method for processing such queries in practice is the TPR-tree. In this paper we first perform an analysis to determine the factors that affect the performance of predictive queries and show that… (More)