Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Institution
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Easy To Find: Creating Query-Based Multi-Document Summaries To Enhance Web Search, Rani Majed Qumsiyeh
Easy To Find: Creating Query-Based Multi-Document Summaries To Enhance Web Search, Rani Majed Qumsiyeh
Theses and Dissertations
Current web search engines, such as Google, Yahoo!, and Bing, rank the set of documents S retrieved in response to a user query Q and display each document with a title and a snippet, which serves as an abstract of the corresponding document in S. Snippets, however, are not as useful as they are designed for, i.e., to assist search engine users to quickly identify results of interest, if they exist, without browsing through the documents in S, since they (i) often include very similar information and (ii) do not capture the main content of the corresponding documents. …
Relationships Among Learning Algorithms And Tasks, Jun Won Lee
Relationships Among Learning Algorithms And Tasks, Jun Won Lee
Theses and Dissertations
Metalearning aims to obtain knowledge of the relationship between the mechanism of learning and the concrete contexts in which that mechanisms is applicable. As new mechanisms of learning are continually added to the pool of learning algorithms, the chances of encountering behavior similarity among algorithms are increased. Understanding the relationships among algorithms and the interactions between algorithms and tasks help to narrow down the space of algorithms to search for a given learning task. In addition, this process helps to disclose factors contributing to the similar behavior of different algorithms. We first study general characteristics of learning tasks and their …
Modeling And Quantitative Analysis Of White Matter Fiber Tracts In Diffusion Tensor Imaging, Xuwei Liang
Modeling And Quantitative Analysis Of White Matter Fiber Tracts In Diffusion Tensor Imaging, Xuwei Liang
University of Kentucky Doctoral Dissertations
Diffusion tensor imaging (DTI) is a structural magnetic resonance imaging (MRI) technique to record incoherent motion of water molecules and has been used to detect micro structural white matter alterations in clinical studies to explore certain brain disorders. A variety of DTI based techniques for detecting brain disorders and facilitating clinical group analysis have been developed in the past few years. However, there are two crucial issues that have great impacts on the performance of those algorithms. One is that brain neural pathways appear in complicated 3D structures which are inappropriate and inaccurate to be approximated by simple 2D structures, …
Class Discovery And Prediction Of Tumor With Microarray Data, Bo Liu
Class Discovery And Prediction Of Tumor With Microarray Data, Bo Liu
All Graduate Theses, Dissertations, and Other Capstone Projects
Current microarray technology is able take a single tissue sample to construct an Affymetrix oglionucleotide array containing (estimated) expression levels of thousands of different genes for that tissue. The objective is to develop a more systematic approach to cancer classification based on Affymetrix oglionucleotide microarrays. For this purpose, I studied published colon cancer microarray data. Colon cancer, with 655,000 deaths worldwide per year, has become the fourth most common form of cancer in the United States and the third leading cause of cancer - related death in the Western world. This research has been focuses in two areas: class discovery, …
Mining Associations Using Directed Hypergraphs, Ramanuja N. Simha
Mining Associations Using Directed Hypergraphs, Ramanuja N. Simha
USF Tampa Graduate Theses and Dissertations
This thesis proposes a novel directed hypergraph based model for any database. We introduce the notion of association rules for multi-valued attributes, which is an adaptation of the definition of quantitative association rules known in the literature. The association rules for multi-valued attributes are integrated in building the directed hypergraph model. This model allows to capture attribute-level associations and their strength. Basing on this model, we provide association-based similarity notions between any two attributes and present a method for finding clusters of similar attributes. We then propose algorithms to identify a subset of attributes known as a leading indicator that …