Computer Sciences Commons^™

Analyzing And Modeling Users In Multiple Online Social Platforms, Roy Lee Ka Wei

Dissertations and Theses Collection (Open Access)

This dissertation addresses the empirical analysis on user-generated data from multiple online social platforms (OSPs) and modeling of latent user factors in multiple OSPs setting.

In the first part of this dissertation, we conducted cross-platform empirical studies to better understand user's social and work activities in multiple OSPs. In particular, we proposed new methodologies to analyze users' friendship maintenance and collaborative activities in multiple OSPs. We also apply the proposed methodologies on real-world OSP datasets, and the findings from our empirical studies have provided us with a better understanding on users' social and work activities which are previously not uncovered …

Distributed Knowledge Discovery For Diverse Data, Hossein Hamooni

Computer Science ETDs

In the era of new technologies, computer scientists deal with massive data of size hundreds of terabytes. Smart cities, social networks, health care systems, large sensor networks, etc. are constantly generating new data. It is non-trivial to extract knowledge from big datasets because traditional data mining algorithms run impractically on such big datasets. However, distributed systems have come to aid this problem while introducing new challenges in designing scalable algorithms. The transition from traditional algorithms to the ones that can be run on a distributed platform should be done carefully. Researchers should design the modern distributed algorithms based on the …

Mining Of Primary Healthcare Patient Data With Selective Multimorbid Diseases, Annette Megerdichian Azad

Electronic Thesis and Dissertation Repository

Despite a large volume of research on the prognosis, diagnosis and overall burden of multimorbidity, very little is known about socio-demographic characteristics of multimorbid patients. This thesis aims to analyze the socio-demographic characteristics of patients with multiple chronic conditions (multimorbidity), focusing on patient groups sharing the same combination of diseases. Several methods were explored to analyze the co-occurrence of multiple chronic diseases as well as the associations between socio-demographics and chronic conditions. These methods include disease pair distributions over gender, age groups and income level quintiles, Multimorbidity Coefficients for measuring the concurrence of disease pairs and triples, and k-modes clustering …

Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs

Theses and Dissertations

NASA Goddard’s LiDAR, Hyperspectral, and Thermal imager provides co-registered remote sensing data on experimental forests. Data mining methods were used to achieve a final tree species classification accuracy of 68% using a combined LiDAR and hyperspectral dataset, and show promise for addressing deforestation and carbon sequestration on a species-specific level.

On Predicting User Affiliations Using Social Features In Online Social Networks, Minh Thap Nguyen

Dissertations and Theses Collection (Open Access)

User profiling such as user affiliation prediction in online social network is a challenging task, with many important applications in targeted marketing and personalized recommendation. The research task here is to predict some user affiliation attributes that suggest user participation in different social groups.

Semi-Automatic Simulation Initialization By Mining Structured And Unstructured Data Formats From Local And Web Data Sources, Olcay Sahin

Computational Modeling & Simulation Engineering Theses & Dissertations

Initialization is one of the most important processes for obtaining successful results from a simulation. However, initialization is a challenge when 1) a simulation requires hundreds or even thousands of input parameters or 2) re-initializing the simulation due to different initial conditions or runtime errors. These challenges lead to the modeler spending more time initializing a simulation and may lead to errors due to poor input data.

This thesis proposes two semi-automatic simulation initialization approaches that provide initialization using data mining from structured and unstructured data formats from local and web data sources. First, the System Initialization with Retrieval (SIR) …

Investigating Data Mining Techniques For Extracting Information From Alzheimer's Disease Data, Vinh Quoc Dang

Theses : Honours

Data mining techniques have been used widely in many areas such as business, science, engineering and more recently in clinical medicine. These techniques allow an enormous amount of high dimensional data to be analysed for extraction of interesting information as well as the construction of models for prediction. One of the foci in health related research is Alzheimer's disease which is currently a non-curable disease where diagnosis can only be confirmed after death via an autopsy. Using multi-dimensional data and the applications of data mining techniques, researchers hope to find biomarkers that will diagnose Alzheimer's disease as early as possible. …

An Investigation Into The Application Of Data Mining Techniques To Characterize Agricultural Soil Profiles, Rowan J. Maddern

Theses : Honours

The advances in computing and information storage have provided vast amounts of data. The challenge has been to extract knowledge from this raw data; this has led to new methods and techniques such as data mining that can bridge the knowledge gap. The research aims to use these new data mining techniques and apply them to a soil science database to establish if meaningful relationships can be found. A data set extracted from the WA Department of Agriculture and Food (DAFW A) soils database has been used to conduct this research. The database contains measurements of soil profile data from …