Practical work involving laboratory experiments is agreed upon to be an essential component of secondary science education. Practical work encompasses a broad range of activity types. The different forms of practical work are not equal in terms of cognitive demand and learning benefit. Inquiry-based investigations provide experience of cognitive…

Shoeprints are a common type of evidence found at crime scenes and are regularly used in forensic investigations. However, their utility is limited by the lack of reference footwear databases that cover the large and growing number of distinct shoe models. Additionally, existing methods for matching crime-scene shoeprints to reference databases…

Bag-of-words is a commonly used text representation method for many text classification applications. However, bag-of-words representation fails to consider the context of the text because it only examines text documents based on the presence of individual words and explores relationships between texts with similar word choices (Bengfort, 2018).…

This research improves the precision of information extraction from free-form text via the use of cognitive-based approaches to natural language processing (NLP). Cognitive-based approaches are an important, and relatively new, area of research in NLP and search, as well as linguistics. Cognitive approaches enable significant improvements in both…

Collaborative information seeking (CIS) is an important aspect of work in organizational settings. Researchers are developing a more detailed understanding of CIS activities and the tools to support them; however, most studies of CIS focus on how people find and retrieve information collaboratively, while overlooking the important question of how…

The overwhelming amount of information available today makes it difficult for users to find useful information and as the solution to this information glut problem, recommendation technologies emerged. Among the several streams of related research, one important evolution in technology is to generate recommendations based on users' own social…

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…

With the adoption of web services in daily life, people have access to tremendous amounts of information, beyond any human's reading and comprehension capabilities. As a result, search technologies have become a fundamental tool for accessing information. Furthermore, the web contains information in multiple languages, introducing another barrier…

The recent technological advancements have led to the availability of a plethora of heterogenous datasets, e.g., images tagged with geo-location and descriptive keywords. An object in these datasets is described by a set of high-dimensional feature vectors. For example, a keyword-tagged image is represented by a color-histogram and a…

Many nutritional assessment techniques, including food frequency questionnaires (FFQs) and 24-hour dietary recalls have innate limitations such as expensive protocols, high respondent burden, and self-reporting biases. Supermarket sales data have shown promise as a new, indirect, inexpensive nutritional assessment method in recent studies. The…

There has been growing interest in building and optimizing retrieval systems with respect to relevance and novelty of information, which together more realistically reflect the usefulness of a system as perceived by the user. How to combine these criteria into a single metric that can be used to measure as well as optimize retrieval systems is an…

Detection of events and actions in video entails substantial processing of very large, even open-ended, video streams. Video data present a unique challenge for the information retrieval community because properly representing video events is challenging. We propose a novel approach to analyze temporal aspects of video data. We consider video data…

This dissertation focuses on developing and evaluating hybrid approaches for analyzing free-form text in the medical domain. This research draws on natural language processing (NLP) techniques that are used to parse and extract concepts based on a controlled vocabulary. Once important concepts are extracted, additional machine learning algorithms,…

The advent of information technology has enabled firms to collect significant amounts of data about individuals and mine the data for developing their strategies. Profiling of individuals is one common use of data collected about them. It refers to using known or inferred information to categorize the type of an individual and to tailor specific…

Current data mining (DM) technology is not domain-specific and therefore rarely generates reliable, business actionable knowledge that can be used to improve the effectiveness of the decision-making process in the banking industry. DM is mainly an autonomous, data-driven process with little focus on domain expertise, constraints, or requirements…