Open Access. Powered by Scholars. Published by Universities.®
Databases and Information Systems Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Spatial Optimization (2)
- Continuous Query Monitoring (1)
- Continuous Query Processing (1)
- Dead-space (1)
- Existing systems (1)
-
- Information leakage (1)
- K-Anonymity (1)
- Location Privacy (1)
- Location information (1)
- Location-Based Services (1)
- Medoid Queries (1)
- Minimum bounding rectangle (1)
- Mobile users (1)
- Moving Object Databases (1)
- On-Demand (1)
- Others (1)
- Performance degradation (1)
- Privacy issue (1)
- Query time (1)
- Real road networks (1)
- Resource Constraint (1)
- Road network (1)
- Shortest path (1)
- Spatial regions (1)
- Transportation network (1)
- User location (1)
- Weighted graph (1)
Articles 1 - 5 of 5
Full-Text Articles in Databases and Information Systems
Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis
Best Upgrade Plans For Large Road Networks, Yimin Lin, Kyriakos Mouratidis
Kyriakos MOURATIDIS
In this paper, we consider a new problem in the context of road network databases, named Resource Constrained Best Upgrade Plan computation (BUP, for short). Consider a transportation network (weighted graph) G where a subset of the edges are upgradable, i.e., for each such edge there is a cost, which if spent, the weight of the edge can be reduced to a specific new value. Given a source and a destination in G, and a budget (resource constraint) B, the BUP problem is to identify which upgradable edges should be upgraded so that the shortest path distance between source and …
Spatial Queries In The Presence Of Obstacles, Jun Zhang, Dimitris Papadias, Kyriakos Mouratidis, Manli Zhu
Spatial Queries In The Presence Of Obstacles, Jun Zhang, Dimitris Papadias, Kyriakos Mouratidis, Manli Zhu
Kyriakos MOURATIDIS
Despite the existence of obstacles in many database applications, traditional spatial query processing utilizes the Euclidean distance metric assuming that points in space are directly reachable. In this paper, we study spatial queries in the presence of obstacles, where the obstructed distance between two points is defined as the length of the shortest path that connects them without crossing any obstacles. We propose efficient algorithms for the most important query types, namely, range search, nearest neighbors, e-distance joins and closest pairs, considering that both data objects and obstacles are indexed by R-trees. The effectiveness of the proposed solutions is verified …
Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis
Continuous Medoid Queries Over Moving Objects, Stavros Papadopoulos, Dimitris Sacharidis, Kyriakos Mouratidis
Kyriakos MOURATIDIS
In the k-medoid problem, given a dataset P, we are asked to choose kpoints in P as the medoids. The optimal medoid set minimizes the average Euclidean distance between the points in P and their closest medoid. Finding the optimal k medoids is NP hard, and existing algorithms aim at approximate answers, i.e., they compute medoids that achieve a small, yet not minimal, average distance. Similarly in this paper, we also aim at approximate solutions. We consider, however, the continuous version of the problem, where the points in P move and our task is to maintain the medoid set on-the-fly …
Spatial Cloaking Revisited: Distinguishing Information Leakage From Anonymity, Kar Way Tan, Yimin Lin, Kyriakos Mouratidis
Spatial Cloaking Revisited: Distinguishing Information Leakage From Anonymity, Kar Way Tan, Yimin Lin, Kyriakos Mouratidis
Kyriakos MOURATIDIS
Location-based services (LBS) are receiving increasing popularity as they provide convenience to mobile users with on-demand information. The use of these services, however, poses privacy issues as the user locations and queries are exposed to untrusted LBSs. Spatial cloaking techniques provide privacy in the form of k-anonymity; i.e., they guarantee that the (location of the) querying user u is indistinguishable from at least k-1 others, where k is a parameter specified by u at query time. To achieve this, they form a group of k users, including u, and forward their minimum bounding rectangle (termed anonymzing spatial region, ASR) to …
Medoid Queries In Large Spatial Databases, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Medoid Queries In Large Spatial Databases, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
Kyriakos MOURATIDIS
Assume that a franchise plans to open k branches in a city, so that the average distance from each residential block to the closest branch is minimized. This is an instance of the k-medoids problem, where residential blocks constitute the input dataset and the k branch locations correspond to the medoids. Since the problem is NP-hard, research has focused on approximate solutions. Despite an avalanche of methods for small and moderate size datasets, currently there exists no technique applicable to very large databases. In this paper, we provide efficient algorithms that utilize an existing data-partition index to achieve low CPU …