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Skip to Search Results- 1Aftergood, Olivia SR
- 1Al Dallal, Ahmed
- 1Behsaz, Babak
- 1Berube, Paul N. J.
- 1Cheng, Hao
- 1Falcao, Alexandre
- 9Department of Computing Science
- 5Department of Electrical and Computer Engineering
- 3Department of Civil and Environmental Engineering
- 1Department of Mathematical and Statistical Sciences
- 1Department of Mechanical Engineering
- 1Department of Pharmacology
- 2Sander, Joerg (Computing Science)
- 1Ardakanian, Omid (Computing Science)
- 1Cockburn, Bruce (Department of Electrical and Computer Engineering)
- 1Deutsch, Clayton (Civil and Environmental Engineering)
- 1Dick, Scott (Department of Electrical and Computer Engineering)
- 1Flannigan, Mike D (Renewable Resources)
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Fall 2012
Recent proliferation of low-cost and lightweight GPS tracking devices led to a large increase in the amounts of collected mobility data. The rapidly emerging field of location-based services requires accurate and informative knowledge mining from these large quantities of data. One such mobility...
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Fall 2017
Density-based clustering methods extract high density clusters which are separated by regions of lower density. HDBSCAN* is an existing algorithm for producing a density-based cluster hierarchy. To obtain clusters from this hierarchy it includes an instance of FOSC(Framework for Optimal Selection...
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Fall 2015
The objective of this thesis is to develop, implement and verify a theoretical framework based upon aggregation and mathematical programming for solving the long-term open pit production planning problem. The goal is to closely estimate the maximum net present value of the operation by providing...
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An Adaptive and Efficient Clustering-based Approach for Content Based Image Retrieval in Image Databases
An Adaptive and Efficient Clustering-based Approach for Content Based Image Retrieval in Image Databases
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Stehling, Renato, Falcao, Alexandre, Nascimento, Mario
Technical report TR01-03. In this paper, we present a new Content-Based Image Retrieval (CBIR) approach which is based on cluster analysis. A distinguishing aspect of CBIR is that it relies on a visual content representation (metadata) of the images. In order to produce such metadata, we propose...
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Fall 2011
An industrial construction enterprise operating in the City of Edmonton wants to improve its bidding strategies that are currently plagued with uncertainty, lack of information and historical price variability. The present research studies a compilation of documents obtained from company archives...
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Fall 2012
In this thesis, we present some approximation algorithms for the following clustering problems: Minimum Sum of Radii (MSR), Minimum Sum of Diameters (MSD), and Unsplittable Capacitated Facility Location. Given a metric (V, d) and an integer k, we consider the problem of partitioning the points...
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Fall 2015
In this thesis, we consider two closely related clustering problems, Min Sum k-Clustering (MSkC) and Balanced k-Median (BkM). In Min Sum k-clustering, one is given a graph and a parameter k, and has to partition the vertices in the graph into k clusters to minimize the sum of pairwise distances...
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Spring 2023
In this thesis, we present Approximation Schemes for the Min Sum k Clustering problem on a number of classes of graph metrics. In Min Sum k Clustering problem introduced by Sahni and Gonzalez [22] in 1976, given a graph G(V, E) with metric edge costs and parameter k, we are asked to partition V...
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Fall 2013
Due to its wide application in various fields, clustering, as a fundamental unsupervised learning problem, has been intensively investigated over the past few decades. Unfortunately, standard clustering formulations are known to be computationally intractable. Although many convex relaxations of...
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Fall 2014
Anomaly detection in spatial time series is a challenging problem with numerous potential applications. A comprehensive anomaly detection approach not only should be able to detect and identify the emerging anomalies, but it also has to characterize the essence of these anomalies by visualizing...