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Distributed frequent hierarchical pattern mining for robust and efficient large-scale association discovery
(University of Missouri--Columbia, 2017)
Frequent pattern mining is a classic data mining technique, generally applicable to a wide range of application domains, and a mature area of research. The fundamental challenge arises from the combinatorial nature of ...
In-memory distributed indexing for large-scale media data retrieval
(University of Missouri--Columbia, 2017)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Multimedia data includes various media types such as text, image and video. Recent research has shown that media data retrieval serves a critical role ...
Refined repetitive searches and long identical multi-species elements in mammals and plants : Insights into structure, function and evolution
(University of Missouri--Columbia, 2010)
All of the information necessary to reproduce a living organism is contained in the DNA of its genome. Within the genomic sequence, there are subsequences called genes that are transcribed into RNA and translated into ...
Temporal mining framework for risk reduction and early detection of chronic diseases
(University of Missouri--Columbia, 2010)
Chronic diseases significantly affect the quality of life of over 25 million Americans and are among the most common health problems. Due to the complexity of these diseases, it is difficult for clinicians to analyze trends ...
Applying visual routines in a cognitive model of visual analysis
(University of Missouri--Columbia, 2010)
Through years of experience, expert image analysts acquire knowledge which allows them to perform an in-depth analysis of images quickly and efficiently. This research aims to build a humanlike framework and cognitive model ...
High-throughput analysis and advanced search for visually-observed phenotypes
(University of Missouri--Columbia, 2012)
The trend in many scientific disciplines today, especially in biology and genetics, is towards larger scale experiments in which a tremendous amount of data is generated. As imaging of data becomes increasingly more popular ...
Distributed association rule mining using an in-memory cluster computer framework
(University of Missouri--Columbia, 2015)
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Association rule mining is a mature area; however, there is much to be done to take full advantage of the massive distributed computing environments ...
High-throughput visual knowledge analysis and retrieval in big data ecosystems
(University of Missouri--Columbia, 2015)
Visual knowledge plays an important role in many highly skilled applications, such as medical diagnosis, geospatial image analysis and pathology diagnosis. Medical practitioners are able to interpret and reason about ...
Semi-automatic exploratory data analytics for actionable discoveries through subgroup mining
(University of Missouri--Columbia, 2017)
People are born with the curiosity to see differences between groups. These differences are useful for understanding the root causes of certain discrepancies, such as populations and diseases. However, without prior knowledge ...