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Full-Text Articles in Computer Sciences
A Data Mining Framework For Improving Student Outcomes On Step 1 Of The United States Medical Licensing Examination, James Clark
A Data Mining Framework For Improving Student Outcomes On Step 1 Of The United States Medical Licensing Examination, James Clark
CCE Theses and Dissertations
Identifying the factors associated with medical students who fail Step 1 of the United States Medical Licensing Examination (USMLE) has been a focus of investigation for many years. Some researchers believe lower scores on the Medical Colleges Admissions Test (MCAT) are the sole factor used to identify failure. Other researchers believe lower course outcomes during the first two years of medical training are better indicators of failure. Yet, there are medical students who fail Step 1 of the USMLE who enter medical school with high MCAT scores, and conversely medical students with lower academic credentials who are expected to have …
Citationally Enhanced Semantic Literature Based Discovery, John David Fleig
Citationally Enhanced Semantic Literature Based Discovery, John David Fleig
CCE Theses and Dissertations
We are living within the age of information. The ever increasing flow of data and publications poses a monumental bottleneck to scientific progress as despite the amazing abilities of the human mind, it is woefully inadequate in processing such a vast quantity of multidimensional information. The small bits of flotsam and jetsam that we leverage belies the amount of useful information beneath the surface. It is imperative that automated tools exist to better search, retrieve, and summarize this content. Combinations of document indexing and search engines can quickly find you a document whose content best matches your query - if …
Parallel Mining Of Association Rules Using A Lattice Based Approach, Wessel Morant Thomas
Parallel Mining Of Association Rules Using A Lattice Based Approach, Wessel Morant Thomas
CCE Theses and Dissertations
The discovery of interesting patterns from database transactions is one of the major problems in knowledge discovery in database. One such interesting pattern is the association rules extracted from these transactions. Parallel algorithms are required for the mining of association rules due to the very large databases used to store the transactions. In this paper we present a parallel algorithm for the mining of association rules. We implemented a parallel algorithm that used a lattice approach for mining association rules. The Dynamic Distributed Rule Mining (DDRM) is a lattice-based algorithm that partitions the lattice into sublattices to be assigned to …