The employment rate of software developers has risen significantly over the last 30 years. As a result, more students are considering computer science as a potential career path. Over the last 15 years, introductory programming course (CS1) enrollment has been increasing at a much faster rate than the increase in the number of CS faculty, with no…

Contemporary research in cognitive and neurological sciences confirms that human brains perform object detection and classification by identifying membership to a single class. When observing a scene with various objects, we can quickly point out and answer queries about the object we recognize, without needing to know what the unknown objects…

This dissertation transforms a set of system complexity reduction problems to feature selection problems. Three systems are considered: classification based on association rules, network structure learning, and time series classification. Furthermore, two variable importance measures are proposed to reduce the feature selection bias in tree…

Quickly accessing the contents of a video is challenging for users, particularly for unstructured video, which contains no intentional shot boundaries, no chapters, and no apparent edited format. We approach this problem in the domain of lecture videos though the use of machine learning, to gather semantic information about the videos; and through…

The size and dynamism of the Web poses challenges for all its stakeholders, which include producers/consumers of content, and advertisers who want to place advertisements next to relevant content. A critical piece of information for the stakeholders is the demographics of the consumers who are likely to visit a given web site. However, predicting…

In its report "To Err is Human", The Institute of Medicine recommended the implementation of internal and external voluntary and mandatory automatic reporting systems to increase detection of adverse events. Knowledge Discovery in Databases (KDD) allows the detection of patterns and trends that would be hidden or less detectable if analyzed by…

The three objectives of this dissertation were to develop a question type model for predicting linguistic features of responses to interview questions, create a tool for linguistic analysis of documents, and use lexical bundle analysis to identify linguistic differences between fraudulent and non-fraudulent financial reports. First, The Moffitt…

Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This dissertation analyzes 411 questions from an introductory Java programming course by reducing the…

High profile cases of fraudulent financial reporting such as those that occurred at Enron and WorldCom have shaken public confidence in the U.S. financial reporting process and have raised serious concerns about the roles of auditors, regulators, and analysts in financial reporting. In order to address these concerns and restore public confidence,…

Targeted email attacks to enable computer network exploitation have become more prevalent, more insidious, and more widely documented in recent years. Beyond nuisance spam or phishing designed to trick users into revealing personal information, targeted malicious email (TME) facilitates computer network exploitation and the gathering of sensitive…