Large real-world graph (a.k.a network, relational) data are omnipresent, in online media, businesses, science, and the government. Analysis of these massive graphs is crucial, in order to extract descriptive and predictive knowledge with many commercial, medical, and environmental applications. In addition to its general structure, knowing what…

The goal of this study is to explore and characterize the effects of using a dynamic graphing utility (DGU) on conceptual understanding and attitudes toward mathematics, measured by the responses of college algebra students to an attitude survey and concepts assessment. Two sections of college algebra taught by the primary researcher are included…

Single-case designs (SCDs) are often used to examine the impact of an intervention over brief periods of time (Kratochwill & Stoiber, 2002; Segool, Brinkman, & Carlson, 2007). The majority of SCDs are inspected using visual analysis (Kromrey & Foster-Johnson, 1996; Morgan & Morgan, 2009). Although the single-case literature…

This dissertation uses a survey methodology to determine the factors behind the decision to adopt cloud storage. The dependent variable in the study is the intent to adopt cloud storage. Four independent variables are utilized including need, security, cost-effectiveness and reliability. The survey includes a pilot test, field test and statistical…

Tabular data is pervasive in the form of spreadsheets and relational databases. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look…

In this thesis, we establish a novel probabilistic framework for the data clustering problem from the perspective of Bayesian decision theory. The Bayesian decision theory view justifies the important questions: what is a cluster and what a clustering algorithm should optimize. We prove that the spectral clustering (to be specific, the…

Networks, such as social networks, are a universal solution for modeling complex problems in real time, especially in the Big Data community. While previous studies have attempted to enhance network processing algorithms, none have paved a path for the development of a persistent storage system. The proposed solution, GraphStore, provides an…

Social networks have become more complex, in particular considering the fact that elements in social networks are not only abstract topological nodes and links, but contain rich social attributes and reflecting diverse social relationships. For example, in a co-authorship social network in a scientific community, nodes in the social network, which…

Graphs are widely used to model structures and relationships of objects in various scientific and commercial fields. Chemical molecules, proteins, malware system-call dependencies and three-dimensional mechanical parts are all modeled as graphs. In this dissertation, we propose to mine and index those graph data to enable fast and scalable search.…

This concurrent embedded mixed methods study investigates the influence of the computer program Tinkerplots™ on 34 preservice elementary teachers' understanding of measures of center and graphical representations of data. Participants' opinions and beliefs about the effectiveness of the program were also explored. At the beginning of the…

Improving foundational academic skills for elementary level students continues to be a challenge for classroom teachers. This study implemented weekly progress monitoring procedures using curriculum-based measurement assessments in conjunction with weekly individual student-teacher graphing and goal-setting conferences to determine the effect the…

In light of the prosperity of online social media, Web users are shifting from data consumers to data producers. To catch the pulse of this rapidly changing world, it is critical to transform online social media data to information and to knowledge. This dissertation centers on the issue of modeling the dynamics of user communities, trending…

Communities, also called clusters or modules, are groups of nodes which probably share common properties and/or play similar roles within a graph. They widely exist in real networks such as biological, social, and information networks. Allowing users to interactively browse and explore the community structure, which is essential for understanding…

Network forensic analysis is a process that analyzes intrusion evidence captured from networked environment to identify suspicious entities and stepwise actions in an attack scenario. Unfortunately, the overwhelming amount and low quality of output from security sensors make it difficult for analysts to obtain a succinct high-level view of complex…

Visual analysis is the primary method of analyzing data in single-subject methodology, which is the predominant research method used in the fields of applied behavior analysis and special education. Previous research on the reliability of visual analysis suggests that judges often disagree about what constitutes an intervention effect. Considering…