Discovery and Effective Use of Frequent Item-set Mining and Association Rules in Datasets

The unprecedented rise in digitized data generation has led to the ever-expanding demand for sophisticated storage and analysis methods capable of handling vast amounts of complex data, much of which is stored within many databases. Owing to the large size of such databases, employment of sophisticated analysis methods, such as data mining and machine learning, becomes necessary to extract useful insights regarding a given system under study. Frequent itemset mining and association rules mining represent two key approaches to mining knowledge stored in databases. However, handling of large databases often leads to time-consuming calculations that necessitate large amounts of memory. In this regard, the development of methods capable of enabling faster, less laborious search or pattern discovery remains a central focus in the field of data mining. Incontestably, such methods could aid in faster processing and knowledge extraction, enabling new breakthroughs in how knowledge is acquired from data and applied in real-world applications. However, real-world applications are often hindered by limitations inherent to currently available algorithms. For instance, many itemset mining algorithms are known to first store a given database as a tree structure in memory. However, such algorithms fail to provide a tight upper bound on the number of nodes that will be generated during the tree building process accordingly, there are no upper bounds governing the amount of memory that is needed to generate such trees. As such, practical implementation of frequent itemset mining algorithms is often restricted by memory consumption. However, despite the importance of memory consumption in the applicability of itemset mining, this factor has not drawn adequate attention from the data mining community and remains as a key challenge in its application. In addition, the majority of algorithms widely used and studied to date are known to require multiple database scans, a factor which restricts their applicability for incremental mining applications. In this regard, the development of an algorithm capable of dynamically mining frequent patterns on-the-fly would open new pathways in data mining, enabling the application of itemset mining methods to new real-world applications, in addition to vastly improving current applications. In this thesis, different approaches are proposed in relation to the above-mentioned limitations currently hampering further progress in this significant area of data mining. First, an upper bound on the number of nodes of well-known tree structures in frequent itemset mining is presented. Second, aiming to overcome the memory consumption constraint, a memory-efficient method to store data processed by the frequent itemset mining algorithm is proposed, where instead of a tree, data is stored in a compact directed graph whose nodes represent items. Third, an algorithm is proposed to overcome costly databases scans in the form of a novel SPFP-tree (single pass frequent pattern tree) algorithm. Lastly, approaches that allow for frequent itemset and association rules to be practically and effectively used in real world applications are proposed. First, the quality and effectiveness of frequent itemset mining in solving a real world facility management problem is examined. Second, with aims of improving the quality of recommendations made to users, as well as to overcome the cold-start problem suffered by new users, a hybrid approach is herein proposed for the application of association rules into recommender systems

III-Nitride Vertical-Cavity Surface-Emitting Lasers: Growth, Fabrication, and Design of Dual Dielectric DBR Nonpolar VCSELs

Vertical-cavity surface-emitting lasers (VCSELs) have a long history of development in GaAs-based and InP-based systems, however III-nitride VCSELs research is still in its infancy. Yet, over the past several years we have made dramatic improvements in the lasing characteristics of these highly complex devices. Specifically, we have reduced the threshold current density from ~100 kA/cm2 to ~3 kA/cm2, while simultaneously increasing the output power from ~10 µW to ~550 µW. These developments have primarily come about by focusing on the aperture design and intracavity contact design for flip-chip dual dielectric DBR III-nitride VCSELs. We have carried out a number of studies developing an Al ion implanted aperture (IIA) and photoelectrochemically etched aperture (PECA), while simultaneously improving the quality of tin-doped indium oxide (ITO) intracavity contacts, and demonstrating the first III-nitride VCSEL with an n-GaN tunnel junction intracavity contact. Beyond these most notable research fronts, we have analyzed numerous other parameters, including epitaxial growth, flip-chip bonding, substrate removal, and more, bringing further improvement to III-nitride VCSEL performance and yield. This thesis aims to give a comprehensive discussion of the relevant underlying concepts for nonpolar VCSELs, while detailing our specific experimental advances. In Section 1, we give an overview of the applications of VCSELs generally, before describing some of the potential applications for III-nitride VCSELs. This is followed by a summary of the different material systems used to fabricate VCSELs, before going into detail on the basic design principles for developing III-nitride VCSELs. In Section 2, we outline the basic process and geometry for fabricating flip-chip nonpolar VCSELs with different aperture and intracavity contact designs. Finally, in Section 3 and 4, we delve into the experimental results achieved in the last several years, beginning with a discussion on the epitaxial growth developments. In Section 4, we discuss the most noteworthy accomplishments related to the nonpolar VCSELs structural design, such as different aperture and intracavity contact developments. Overall, this thesis is focused on the nonpolar VCSEL, however our hope is that many of the underlying insights will be of great use for the III-nitride VCSELs community as a whole. Throughout this report, we have taken great effort to highlight the future research fronts that would advance the field of III-nitride VCSELs generally, with the goal of illuminating the path forward for achieving efficient CW operating III-nitride VCSELs