Neuroscience can greatly benefit from using novel methods in computer science and informatics, which enable knowledge discovery in unexpected ways. Currently one of the biggest challenges in Neuroscience is to map the functional circuitry of the brain. The applications of this goal range from understanding structural reorganization of neurons to…

Cyberlearning presents numerous challenges such as the lack of personal and assessment-driven learning, how students are often puzzled by the lack of instructor guidance and feedback, the huge volume of diverse learning materials, and the inability to zoom in from the general concepts to the more specific ones, or vice versa. Intelligent tutoring…

Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to…

Knowledge elicitation from human beings is important for many fields, such as decision support systems, risk communication, and customer preference studying. Traditional approaches include observations, questionnaires, structured and semi-structured interviews, and group discussions. Many publications have been studying different techniques for a…

The Dublin Core "1:1 Principle" asserts that "related but conceptually different entities, for example a painting and a digital image of the painting, are described by separate metadata records" (Woodley et al., 2005). While this seems to be a simple requirement, studies of metadata quality have found that cultural heritage…

Scientists produce research resources that are useful to future research and innovative efforts. In a typical scientific scenario, the results created by a collaborative team often include numerous artifacts, observations and relationships relevant to research findings, such as programs that generate data, parameters that impact outputs, workflows…

Data in many growing fields has an underlying network structure that can be taken advantage of. In this dissertation we apply data and network science to problems in the domains of systems biology and healthcare. Data challenges in these fields include noisy, heterogeneous data, and a lack of ground truth. The primary thesis of this work is that…

Previous cognitive models of memory have not comprehensively taken into account the internal cognitive load of chunking isolated information and have emphasized the external cognitive load of visual presentation only. Under the Virk Long Term Working Memory Multimedia Model of cognitive load, drawing from the Cowan model, students presented with…

Intelligent Tutoring Systems (ITS) have a significant educational impact on student's learning. However, researchers report time intensive interaction is needed between ITS developers and domain-experts to gather and represent domain knowledge. The challenge is augmented when the target domain is ill-defined. The primary problem resides in…

Because many words of a language have more than one meaning, readers regularly need to disambiguate words during sentence comprehension. Using priming, eye-tracking, and event-related brain potentials, this thesis tested whether readers differently disambiguate words with semantically related meanings like "wire" and "cone,"…

This mixed method study combined the paradigms of quantitative and qualitative research to examine how iPads are used from teachers' perspectives. In the first phase, the researcher collected and analyzed the quantitative data from classroom observations. The second phase consisted of collecting and analyzing the qualitative data to help explain,…

In this thesis, we study the importance of background knowledge in relation extraction systems. We not only demonstrate the benefits of leveraging background knowledge to improve the systems' performance but also propose a principled framework that allows one to effectively incorporate knowledge into statistical machine learning models for…

Social media provide a multitude of opportunities for knowledge contribution and sharing. However, the content reliability issue has caused comprehensive attention, especially on credible social media, such as Wikipedia. Despite Wikipedia's success with the open editing model, dissenting voices give rise to unreliable content due to two…

This thesis work is mainly focused on two problems related to improving accessibility of information graphics for visually impaired users. The first problem is automated analysis of information graphics for information extraction and the second problem is multi-modal representations for accessibility. Information graphics are graphical…

The World Wide Web has been revolutionizing how investors produce and consume information while participating in financial markets. Both the amount of information and the speed it flows around have achieved unprecedented magnitudes. The preeminent change is the growth of investor communities on the social web, which give rise to multidimensional…