Data Mining Using Relational Database Management Systems

Software packages providing a whole set of data mining and machine learning algorithms are attractive because they allow experimentation with many kinds of algorithms in an easy setup. However, these packages are often based on main-memory data structures, limiting the amount of data they can handle. In this paper we use a relational database as secondary storage in order to eliminate this limitation. Unlike existing approaches, which often focus on optimizing a single algorithm to work with a database backend, we propose a general approach, which provides a database interface for several algorithms at once. We have taken a popular machine learning software package, Weka, and added a relational storage manager as back-tier to the system. The extension is transparent to the algorithms implemented in Weka, since it is hidden behind Weka’s standard main-memory data structure interface. Furthermore, some general mining tasks are transfered into the database system to speed up execution. We tested the extended system, refered to as WekaDB, and our results show that it achieves a much higher scalability than Weka, while providing the same output and maintaining good computation time

Male circumcision and prevalence of genital human papillomavirus infection in men : a multinational study

Background: Accumulated evidence from epidemiological studies and more recently from randomized controlled trials suggests that male circumcision (MC) may substantially protect against genital HPV infection in men. The purpose of this study was to assess the association between MC and genital HPV infection in men in a large multinational study. Methods: A total of 4072 healthy men ages 18-70 years were enrolled in a study conducted in Brazil, Mexico, and the United States. Enrollment samples combining exfoliated cells from the coronal sulcus, glans penis, shaft, and scrotum were analyzed for the presence and genotyping of HPV DNA by PCR and linear array methods. Prevalence ratios (PR) were used to estimate associations between MC and HPV detection adjusting for potential confounders. Results: MC was not associated with overall prevalence of any HPV, oncogenic HPV types or unclassified HPV types. However, MC was negatively associated with non-oncogenic HPV infections (PR 0.85, 95% confident interval: 0.76-0.95), in particular for HPV types 11, 40, 61, 71, and 81. HPV 16, 51, 62, and 84 were the most frequently identified genotypes regardless of MC status. Conclusions: This study shows no overall association between MC and genital HPV infections in men, except for certain non-oncogenic HPV types for which a weak association was found. However, the lack of association with MC might be due to the lack of anatomic site specific HPV data, for example the glans penis, the area expected to be most likely protected by MC

A Common SMAD7 Variant Is Associated with Risk of Colorectal Cancer: Evidence from a Case-Control Study and a Meta-Analysis

<div><h3>Background</h3><p>A common genetic variant, rs4939827, located in <em>SMAD7</em>, was identified by two recent genome-wide association (GWA) studies to be strongly associated with the risk of colorectal cancer (CRC). However, the following replication studies yielded conflicting results.</p> <h3>Method and Findings</h3><p>We conducted a case-control study of 641 cases and 1037 controls in a Chinese population and then performed a meta-analysis, integrating our and published data of 34313 cases and 33251 controls, to clarify the relationship between rs4939827 and CRC risk. In our case-control study, the dominant model was significant associated with increased CRC risk [Odds Ratio (OR) = 1.46; 95% confidence interval (95% CI), 1.19–1.80]. The following meta-analysis further confirmed this significant association for all genetic models but with significant between-study heterogeneity (all <em>P</em> for heterogeneity <0.1). By stratified analysis, we revealed that ethnicity, sample size, and tumor sites might constitute the source of heterogeneity. The cumulative analysis suggested that evident tendency to significant association was seen with adding study samples over time; whilst, sensitive analysis showed results before and after removal of each study were similar, indicating the highly stability of the current results.</p> <h3>Conclusion</h3><p>Results from our case-control study and the meta-analysis collectively confirmed the significant association of the variant rs4939827 with increased risk of colorectal cancer. Nevertheless, fine-mapping of the susceptibility loci defined by rs4939287 should be imposed to reveal causal variant.</p> </div

Regulation versus competition : an assessment of regulation’s impacts on title insurance premiums

textThis study uses a multilevel model of change to assess the effects of five distinguished regulation styles in title insurance on insurance premiums. This study finds that the states promulgating title insurance premiums have higher charges than the states allowing free competition in the title insurance market. The other regulation styles do not have significantly different impacts on title insurance premiums from free competition. In addition, market characteristics such as home sales, housing price, and property value can also influence title insurance premiums. This study explains the title insurance premium variation among states. The research outcomes can also provide insights into the ongoing regulatory reform in title insurance, in particular in the states using the promulgation regulation style.Statistic

An empirical evaluation on how regulatory and market factors affect title insurance charges

textThe objective of this dissertation is to evaluate how regulatory and market factors affect title insurance charges in different states. As substantial components of home purchase closing costs, title insurance charges have been controversial for decades, and both practitioners and analysts have pointed out apparent variations in title insurance charges among states. Although existing studies have suggested a set of regulatory and market factors as explanations for these among-state variations, empirical evaluations are limited. To fill in this gap, this dissertation empirically assesses whether these factors influence title insurance charges. The research outcomes of these dissertation indicate that after taking into account market factors such as services included in title insurance charges, title-related losses, property values, state populations, home sale volumes, housing prices, and income levels, regulation styles can still partially explain the title insurance charge variations in different states. In particular, states with promulgation regulation can have a higher average title insurance charge than states allowing free competition. This dissertation also tests whether regulation affects title insurance charges by influencing competition in the market and whether regulators' characteristics are related to the effect of regulation on charges. The test results imply that appointed commissioners can be associated with a higher average title insurance charge than elected commissioners. This dissertation provides insights into the title insurance regulatory reform in different states. More broadly, one methodology (multiple model for change) used in this dissertation simultaneously assesses regulation's over-time and state-by-state effects on title insurance charges, which contributes to the development of regulation evaluation methods. The outcomes of this dissertation can also provide empirical evidence to the theoretical debate of regulation versus competition.Public Polic

Data mining with relational database management systems

With the increasing demands of transforming raw data into information and knowledge, data mining becomes an important field to the discovery of useful information and hidden patterns in huge datasets. Both machine learning and database research have made major contributions to the field of data mining. However, there is still little effort made to improve the scalability of algorithms applied in data raining tasks. Scalability is crucial for data mining algorithms, since they have to handle large datasets quite often. In this thesis we take a step in this direction by extending a popular machine learning software, Weka3.4, to handle large datasets that can not fit into main memory by relying on relational database technology. Weka3.4-DB is implemented to store the data into and access the data from DB2 with a loose coupling approach in general. Additionally, a semi-tight coupling is applied to optimize the data manipulation methods by implementing core functionalities within the database. Based on the DB2 storage implementation, Weka3.4-DB achieves better scalability, but still provides a general interface for developers to implement new algorithms without the need of database or SQL knowledge