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1.
Modeling alternatives to solve the connected graph k-clustering problem
by Es-Sakli, Nada, M.S.  Lehigh University. 2011: 74 pages; 1488515.
2.
Weighted clustering ensembles
by Al-Razgan, Muna Saleh, Ph.D.  George Mason University. 2008: 146 pages; 3323309.
3.
Clustering transient data streams by example and by variable
by Chaovalit, Pimwadee, Ph.D.  University of Maryland, Baltimore County. 2009: 224 pages; 3359104.
4.
Studies of spatial clustering of inertial particles in turbulence
by Saw, Ewe Wei, Ph.D.  Michigan Technological University. 2008: 164 pages; 3339459.
5.
Assessing the Robustness of Clustering Methods for use in Vegetation Classification
by Dell, Noah David, M.S.  Southern Illinois University at Edwardsville. 2017: 108 pages; 10275943.
7.
Clustering and entity resolution for semi-structured data
by Zhao, Chuan, Ph.D.  Washington State University. 2011: 208 pages; 3495962.
8.
Stochastic Data Clustering
by Wessell, Charles David, Ph.D.  North Carolina State University. 2011: 102 pages; 3479609.
10.
Applications of k-means and spectral clustering to hyperspectral video sequences
by Sunu, Justin, M.S.  California State University, Long Beach. 2014: 72 pages; 1526959.
11.
Model Based Clustering Algorithms with Applications
by Wei, Wutao, Ph.D.  Purdue University. 2018: 124 pages; 10830711.
12.
Botnet Detection Using Graph Based Feature Clustering
by Akula, Ravi Kiran, M.S.  Mississippi State University. 2018: 69 pages; 10751733.
13.
Clustering datasets with singular value decomposition
by Douglas, Emmeline P., M.S.  College of Charleston. 2008: 85 pages; 1461189.
14.
Solution of Constrained Clustering Problems Through Homotopy Tracking
by Easterling, David R., Ph.D.  Virginia Polytechnic Institute and State University. 2014: 101 pages; 10595248.
15.
Probabilistic Clustering Ensemble Evaluation for Intrusion Detection
by McElwee, Steven M., Ph.D.  Nova Southeastern University. 2018: 166 pages; 10844875.
16.
Clustering of Large-Scale Protein Datasets
by Abnousi, Armen, Ph.D.  Washington State University. 2018: 118 pages; 10641432.
17.
Clustering, searching and evaluating biological sequence data
by Ghodsi, Mohammadreza, Ph.D.  University of Maryland, College Park. 2012: 104 pages; 3543455.
18.
Clustering digital ink content to assist with the grading of student work
by Hatfield, Jared, M.Eng.  University of Louisville. 2011: 65 pages; 1504211.
19.
Time-Slicing of Movement Data for Efficient Trajectory Clustering
by Edens, Jared M., M.S.  Southern Illinois University at Edwardsville. 2014: 46 pages; 1560760.
20.
Clustering of Cyclic-Nucleotide-Gated Channels in Olfactory Cilia
by Flannery, Richard, Ph.D.  University of Cincinnati. 2006: 98 pages; 10857134.
22.
Two Statistical Methods for Clustering Medicare Claims into Episodes of Care
by Gibbons, Robert Lyon, Ph.D.  University of California, Berkeley. 2011: 135 pages; 3473890.
24.
25.
High-speed tracking of rupture and clustering in freely falling granular streams
by Royer, John R., Ph.D.  The University of Chicago. 2009: 110 pages; 3369460.
27.
Clustering algorithms for next-generation sequencing data from heterogenous populations
by Prabhakara, Shruthi, Ph.D.  The Pennsylvania State University. 2012: 126 pages; 3737327.
28.
An enhanced low energy adaptive clustering hierarchy protocol for wireless sensor networks
by Golwalkar, Ankit, M.S.  California State University, Long Beach. 2016: 48 pages; 10137447.
29.
Probing Integrin Specificity in regards to Clustering Dynamics on Soft and Stiff Matrices
by Gile, Ryan Edward, M.S.  University of California, San Francisco. 2011: 73 pages; 1490823.
30.
A comparison of particle swarm optimization algorithms in data clustering
by Chung, Yu-Kuang, M.S.  California State University, Long Beach. 2010: 69 pages; 1486378.
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