In the big data era, we have witnessed the explosion of scholarly literature. This explosion has imposed challenges to the retrieval of bibliographic information. Retrieval of intended bibliographic information has become challenging due to the overwhelming search results returned by bibliographic information retrieval systems for given input…

There has been vast and growing amount of healthcare data especially with the rapid adoption of electronic health records (EHRs) as a result of the HITECH act of 2009. It is estimated that around 80% of the clinical information resides in the unstructured narrative of an EHR. Recently, natural language processing (NLP) techniques have offered…

This dissertation addresses the problems of program comprehension to support the evolution of large-scale software systems. The research concerns how software engineers locate features and concepts along with categorizing changes within very large bodies of source code along with their versioned histories. More specifically, advanced Information…

The study investigated research topics of doctoral dissertations that examined issues in distance learning from 2000-2014. Twelve reviews of research on distance learning, spanning from 1997-2015, were identified. It was found that only one of these reviews of research (Davies, Howell, & Petri, 2010) looked at doctoral dissertations. The…

We live in an era of information overload. From online news to online shopping to scholarly research, we are inundated with a torrent of information on a daily basis. With our limited time, money and attention, we often struggle to extract actionable knowledge from this deluge of data. A common approach for addressing this challenge is…

Identifying topics of a textual document is useful for many purposes. We can organize the documents by topics in digital libraries. Then, we could browse and search for the documents with specific topics. By examining the topics of a document, we can quickly understand what the document is about. To augment the traditional manual way of topic…

The construction industry is a knowledge intensive industry. Thousands of documents are generated by construction projects. Documents, as information carriers, must be managed effectively to ensure successful project management. The fact that a single project can produce thousands of documents and that a lot of the documents are generated in a…

The Institute of Medicine has stated that legal structures and the authority vested in health agencies and other partners within the public health system are essential to improving the public's health. Variation between the laws of different jurisdictions within the United States allows for natural experimentation and research into their…

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…

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 objective of this work is to examine the efficacy of natural language processing (NLP) in summarizing bibliographic text for multiple purposes. Researchers have noted the accelerating growth of bibliographic databases. Information seekers using traditional information retrieval techniques when searching large bibliographic databases are often…

The research investigated whether a Latent Semantic Analysis (LSA)-based approach to image retrieval can map pixel intensity into a smaller concept space with good accuracy and reasonable computational cost. From a large set of M computed tomography (CT) images, a retrieval query found all images for a particular patient based on semantic…

One of the most critical steps to integrating heterogeneous e-Business applications using different XML schemas is schema matching, which is known to be costly and error-prone. Many automatic schema matching approaches have been proposed, but the challenge is still daunting because of the complexity of schemas and immaturity of technologies in…

In the current millennium, extensive use of computers and the internet caused an exponential increase in information. Few research areas are as important as information extraction, which primarily involves extracting concepts and the relations between them from free text. Limitations in the size of training data, lack of lexicons and lack of…

Along with the greater productivity that CAD automation provides nowadays, the product data of engineering applications needs to be shared and managed efficiently to gain a competitive edge for the engineering product design. However, exchanging and sharing the heterogeneous product data is still challenging. This dissertation first presents a…