Open Access. Powered by Scholars. Published by Universities.®
Databases and Information Systems Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Algorithms (1)
- Approximate algorithms (1)
- Cardinalities (1)
- Continuous Query Monitoring (1)
- Data query (1)
-
- Database management (1)
- Direct neighbors (1)
- Exact algorithms (1)
- Heuristic techniques (1)
- Information retrieval (1)
- Internship assignment (1)
- Low-dimensional search (1)
- Multiple simultaneous requests (1)
- Nearest neighbors (1)
- Network monitoring (1)
- Novel strategies (1)
- Number distribution (1)
- Number partitioning (1)
- Others (1)
- Query optimization (1)
- Road Network Databases (1)
- Road networks (1)
- Spatial Optimization (1)
- Subset sum (1)
- Window query (1)
Articles 1 - 5 of 5
Full-Text Articles in Databases and Information Systems
Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Direct Neighbor Search, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Kyriakos MOURATIDIS
In this paper we study a novel query type, called direct neighbor query. Two objects in a dataset are direct neighbors (DNs) if a window selection may exclusively retrieve these two objects. Given a source object, a DN search computes all of its direct neighbors in the dataset. The DNs define a new type of affinity that differs from existing formulations (e.g., nearest neighbors, nearest surrounders, reverse nearest neighbors, etc.) and finds application in domains where user interests are expressed in the form of windows, i.e., multi-attribute range selections. Drawing on key properties of the DN relationship, we develop an …
Heuristic Algorithms For Balanced Multi-Way Number Partitioning, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Heuristic Algorithms For Balanced Multi-Way Number Partitioning, Jilian Zhang, Kyriakos Mouratidis, Hwee Hwa Pang
Kyriakos MOURATIDIS
Balanced multi-way number partitioning (BMNP) seeks to split a collection of numbers into subsets with (roughly) the same cardinality and subset sum. The problem is NP-hard, and there are several exact and approximate algorithms for it. However, existing exact algorithms solve only the simpler, balanced two-way number partitioning variant, whereas the most effective approximate algorithm, BLDM, may produce widely varying subset sums. In this paper, we introduce the LRM algorithm that lowers the expected spread in subset sums to one third that of BLDM for uniformly distributed numbers and odd subset cardinalities. We also propose Meld, a novel strategy for …
A Fair Assignment Algorithm For Multiple Preference Queries, Leong Hou U, Nikos Mamoulis, Kyriakos Mouratidis
A Fair Assignment Algorithm For Multiple Preference Queries, Leong Hou U, Nikos Mamoulis, Kyriakos Mouratidis
Kyriakos MOURATIDIS
Consider an internship assignment system, where at the end of each academic year, interested university students search and apply for available positions, based on their preferences (e.g., nature of the job, salary, office location, etc). In a variety of facility, task or position assignment contexts, users have personal preferences expressed by different weights on the attributes of the searched objects. Although individual preference queries can be evaluated by selecting the object in the database with the highest aggregate score, in the case of multiple simultaneous requests, a single object cannot be assigned to more than one users. The challenge is …
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 …
Continuous Nearest Neighbor Monitoring In Road Networks, Kyriakos Mouratidis, Man Lung Yiu, Dimitris Papadias, Nikos Mamoulis
Continuous Nearest Neighbor Monitoring In Road Networks, Kyriakos Mouratidis, Man Lung Yiu, Dimitris Papadias, Nikos Mamoulis
Kyriakos MOURATIDIS
Recent research has focused on continuous monitoring of nearest neighbors (NN) in highly dynamic scenarios, where the queries and the data objects move frequently and arbitrarily. All existing methods, however, assume the Euclidean distance metric. In this paper we study k-NN monitoring in road networks, where the distance between a query and a data object is determined by the length of the shortest path connecting them. We propose two methods that can handle arbitrary object and query moving patterns, as well as °uctuations of edge weights. The ¯rst one maintains the query results by processing only updates that may invalidate …