Secondary Features Of Importance For A Url Ranking, Atajan Abdyyev

Dissertations and Theses

This paper investigates the impact of secondary ranking factors on webpage relevance and rankings in the context of Search Engine Optimization (SEO), focusing on the jewelry domain within the United States e-commerce market. By generating a keyword list related to jewelry and retrieving top URLs from Google's search results, the study employs machine learning models including XGBoost, CatBoost, and Linear Regression to identify key features influencing webpage relevance and rankings.The findings highlight specific optimal ranges for features like Outlinks, Unique Inlinks, Flesch Reading Ease Score, and others, indicating their significant impact on better rankings. Notably, Random Forest model performed best …

Decorrelated Deep Neural Networks: Learning Bias Invariant & Scanner Independent Features, And Causal Relationships Using A Novel Deep Learning Methods Based On Distance Correlation, Pranita Patil

Dissertations and Theses

Advancements in deep learning or deep neural networks have made it possible to reach expert-level performance in a variety of applications, even in challenging situations. However, a central challenge in all deep learning, as well as machine learning applications, is dealing with its dependency on the quality of data which can be significantly impacted by biases, confounders, and irrelevant variations in data which leads to spurious relationships and erroneous decisions. The main purpose of this dissertation is to build a robust deep learning model which considers and mitigates these biases. Another challenge with the deep learning model is learning associations …

Predicting Absenteeism Of Female Students In Alabama, Funmilola Okelana

Dissertations and Theses

Abstract

Students are chronically absent when they miss at least 15 days of the school year. Past researchers have identified income and environment as factors that affect school absenteeism. Alabama is a poor state with a high crime rate. The hypothesis for this research is that the absenteeism of female students in Alabama is high. Do we reject or fail to reject this hypothesis. If we fail to reject this hypothesis, then what other factors can affect absenteeism in schools? How can we best predict the absenteeism of female students in Alabama? What is the effect of bad data on …

Extracting Signal From The Noisy Environment Of An Ecosystem, Emily Wefelmeyer, Pranita Pramod Patil, Sridhar Reddy Ravula, Kevin M. Purcell, Ziyuan Huang, Igor Pilja

Other Student Works

The collection and storage of environmental and ecological data by researchers, government agencies and stewardship groups over the last decade has been remarkable. The proportional challenge to this data accretion lies in capitalizing on these resources for significant gain for both stewards and stakeholders. These trends highlight the role of data science as a critical component to the future of data-driven environmental management. Most critical are models of how data scientists can collaborate with policy makers and stewards to offer tools that leverage data and facilitate decisions. Our project aims to show how a successful collaboration between a management group, …

Presidential Job Approval Rating Analysis Through Social Media, Subramanian Venkataraman, Subramanian Venkataraman

Dissertations and Theses

The aim of this study is to identify patterns in President Trump’s approval in the

Twitter universe through Social Media and Sentiment Analysis, and compare

against scientific polling to get meaningful insights on the limitations of Social

Media Analytics. For the purposes for this exercise, results from scientific polling

will be considered the true measure of approval, and will be used as control. In

order to perform sentiment analysis, we have used supervisory learning using

Naive Bayes Classifier algorithm which produced 0.862667 accuracy levels.

Speech Processing Approach For Diagnosing Dementia In An Early Stage, Roozbeh Sadeghian, J. David Schaffer, Stephen A. Zahorian

Faculty Works

The clinical diagnosis of Alzheimer’s disease and other dementias is very challenging, especially in the early stages. Our hypothesis is that any disease that affects particular brain regions involved in speech production and processing will also leave detectable finger prints in the speech. Computerized analysis of speech signals and computational linguistics have progressed to the point where an automatic speech analysis system is a promising approach for a low-cost non-invasive diagnostic tool for early detection of Alzheimer’s disease.

We present empirical evidence that strong discrimination between subjects with a diagnosis of probable Alzheimer’s versus matched normal controls can be achieved …

Strategies For Using Data Analytics In Testing The Readability Levels Of Textbooks: It’S Time To Get Serious, Emily Wefelmeyer, Mary Beth Backus

Other Student Works

The idea that education in America is deteriorating is emotionally charged and controversial. While there is no disputing that education levels in the United States continue to rise, there is also a pervasive notion that this was accomplished by gradually reducing the readability level and general difficulty of textbooks. One tool often employed in the defense of education is the employment of readability indices in the evaluation of textbooks. There are a variety of these readability indices that serve the purpose of indicating a grade level for a particular piece of writing (Kinkaid, et. al., 1975). It’s relatively easy to …

Towards An Automated Screening Tool For Pediatric Speech Delay, Roozbeh Sadeghian, Stephen A. Zahorian

Faculty Works

Speech delay is a childhood language problem that sometimes is resolved on its own but sometimes may cause more serious language difficulties later. This leads therapists to screen children for detection at early ages in order to eliminate future problems. Using the Goldman-Fristoe Test of Articulation (GFTA) method, therapists listen to a child's pronunciation of certain phonemes and phoneme pairs in specified words and judge the child's stage of speech development. The goal of this paper is to develop an Automatic Speech Recognition (ASR) tool and related speech processing methods which emulate the knowledge of speech therapists. In this paper …