Artificial Intelligence for Kentucky

DAY 1

Improving Ecosystem Quality Through Data Mining Application

Ryan Boone was awarded ($5,000). Dr. Zhuhadar mentored Ryan in this research.
Ryan presented at the 2019 Teradata Universe, Anaheim, CA.
Related presentation: What Data Analytics Can Do for You, Mammoth Cave Research Symposia, 11th Research Symposium: https://digitalcommons.wku.edu/cgi/viewcontent.cgi?article=1140&context=mc_reserch_symp

Lily Zhuhadar, Kirk Atkinson, Albert Meier, and Ouida Meier

Abstract. In this presentation, we describe how the WKU Initiative for Applied Data Analytics (ADA) can play a crucial role in helping YOU as a business organization or an environmental research entity make sense of YOUR data and how to best utilize it. For example, we will present our first grant proposal, “Designing and Implementing a Cloud-based Repository for the WKU Green River Preserve: Moving from Entrenched Data Structure to Semantic Web.” The ADA Initiative recently offered its Data Mining and Predictive Analytics research services to WKU Green River Preserve (GRP). Dr. Albert Meier (Executive Director of the GRP) and Dr. Ouida Meier have decades of experience and dedicated efforts to host numerous projects focused on the Preserve or include it as a study site in a larger project. Through this grant proposal, we worked with Dr. Meier to capture, organize, store, and release various datasets accumulated and growing at an accelerated rate at the Green River Preserve (GRP). In this presentation, we will describe what Data Analytics can do for GRP and or for YOU!

OSP Award #: SP240

Risk Analysis: Profiling Customers

Abstract: Lending Club is a peer-to-peer marketplace where borrowers and investors are matched together. The goal of the Lending Club is to reduce the costs associated with these banking transactions and make borrowing less expensive and investment more engaging. Lending Club provides data on loans approved and rejected since 2007, including the assigned interest rate and the type of loan. To help the Lending Club produce effective matches between borrowers and investors, we looked at what factors are weighed heavier than others when determining if the borrowers have been accepted or rejected for loans. In determining which factors impact the loan status, the Lending Club could narrow down its borrowers by these factors to provide the best matches cost-effectively. We used the K-means clustering algorithm and regression models to model the results and determine these characteristics.

Morgan Lyon Hayes was awarded a FUSE Grant ($3,000). Dr. Zhuhadar mentored Morgan on this research from January 2019 until April 2021. Ms. Hayes's research was accepted at the 2021 INFORMS Business Analytics Conference, April 26-28, 2021, in Denver, Colorado.

FUSE Award #: 20-SP250

Target Marketing: Predicting Pregnant Customers Using Analytics

Abstract: Retailmart wanted to know which of their sampled customers are most likely to be predicted to be pregnant. Through preliminary data mining research, I could indicate which customers in the given sample data are most likely to be pregnant based on their current purchases. The attributes that proved to be the top predictors are Folic Acid, Prenatal Yoga, Prenatal Vitamins, Birth Control, Maternity Clothes, and Ginger Ale. This analysis can save Retailmart thousands of dollars in advertising costs. Instead of sending out coupons to thousands of people, they can now narrow their Marketing Campaign to the most likely to respond. Predictive analytics can go so much further than predicting pregnancy; it can be used to maximize the marketing campaign’s effectiveness while simultaneously aiding in increasing profits and saving the company money. Using the customers’ purchase history dataset, I first used the Logistic Regression model to get a Lift Chart. Also, I determined which variables were unnecessary to the prediction and excluded them from my determining model. Finally, I presented the most influential predicting attributes in this case study.

Abigail McGraw was awarded a FUSE Grant ($3,000). Dr. Zhuhadar mentored Abby on this research from January 2019 until April 2021. Abby's research was accepted at the 2021 INFORMS Business Analytics Conference, April 26-28, 2021, in Denver, Colorado.

FUSE Award #: 20-SP250

Using Machine Learning Algorithms to Detect Financial Fraud

Abstract:

New fraud detection methods are constantly evolving using big data, stream computing, and machine learning technologies (Vona, 2017). Companies such as SAS and IBM are heavily investing in building real-time fraud detection solutions for organizations, banks, and governments. While IBM announced that its solution could detect online fraud incidents before they occur, this type of solution is costly (Scuotto, Ferraris, & Bresciani, 2016). In our proposed research study, I do not consider a real-time solution. Still, I examine historical transaction data from SAS Institute to build a model that can detect fraudulent patterns. Hence, this research investigates irregularities in historical data to prove that the enterprise is not maintaining its accounting system in agreement with its procedures.

More specifically, the research process starts with the theoretical consideration known as Benford’s law (the law of anomalous numbers). This law was introduced in 1938 by Frank Benford to detect some types of patterns in numbers. In short, Benford’s law assumes a relationship between the frequency of a specific digit and its magnitude. This phenomenon can be used in accounting data to detect fraud. Using Benford’s law, I can see whether or not a customer (or a sales manager) exhibits a behavior (over time) that corresponds with the normal pattern of behavior.

Ian Hamilton was awarded a FUSE Grant ($3,000). Dr. Zhuhadar mentored Ian on this research. Ian received recognition awards at the 2019 Poster-at-the-Capitol (Lexington, KY) from the Senate of the Commonwealth of Kentucky and the House of Representatives of the Commonwealth of Kentucky.

FUSE Award #: 19-SP263

Determining the Effect and Detriment through Sentiment Analysis

Abstract:

Computerized text analysis can often pick up these linguistic features better than humans. This project proposes utilizing sentiment analysis better to understand the relationship between language and school shootings. This research aims to analyze the semantics surrounding terrorism, including nonpolitical attacks, such as school shootings. I believe additional research is necessary for looking at the people’s sentiment following and preceding an attack. GDP does not measure the isolation, insecurity, and despair that occurs after an attack immediately; it only tracks the movement of capital. The effects of terrorism are much larger than that. In this research, I plan to (1) perform sentiment analyses on textual data surrounding terrorist attacks (i.e., Twitter, Facebook) and (2) determine the affective state of the sentences: whether or not the messages contain positive, neutral, or negative sentiment concerning the attacks.

Kyla Scanlon was awarded a FUSE Grant ($3,000). Dr. Zhuhadar mentored Kyla on this research. Kyla received recognition awards at the 2018 Poster-at-the-Capitol (Lexington, KY) from the Senate of the Commonwealth of Kentucky and the House of Representatives of the Commonwealth of Kentucky. Also, Kyla presented her research at the 2018 Teradata Universe (Las Vegas, NV).

FUSE Award #: 18-SP280

Discovering pathways to success in business majors

Kyler Hart was awarded a FUSE Grant ($3,000). Dr. Zhuhadar mentored Kyker on this research.

Kyler presented his research at the 2017 Marketing Science Conference, Fox School of Business, Temple University, Philadelphia, PA.

FUSE Award #: 18-SP265

Too big to fail? Or too blind to see? Profit Analysis

Zach Ross was awarded a FUSE grant ($3,000). Dr. Zhuhadar mentored Zach on this research.

He was one of the three finalists at the INFORMS’ International Conference Competition, Hawaii, 2016.
Also, Zach won his session at the 2016 Annual WKU Student Research Conference.

FUSE Award #: 16-SP280

Using predictive analytics to better enhance consumer lending

Corey Travis was awarded a FUSE grant ($3,000). Dr. Zhuhadar mentored Corey on this research.

Corey was one of the three finalists at the INFORMS’ International Conference Competition, Hawaii, 2016.
Also, Corey won his session at the 2016 Annual WKU Student Research Conference.

FUSE Award #: 16-SP274

Who Wants My Product? Affinity-Based Marketing

Cody Kirk was awarded a FUSE grant ($3,000). Dr. Zhuhadar mentored Cody on this research.

He won the best poster session at the 2015 GFCB REACH Week.
He received recognition awards at the 2015 Poster-at-the-Capitol (Lexington, KY) from the Senate of the Commonwealth of Kentucky and the House of Representatives of the Commonwealth of Kentucky.
He also won the second round at the 2015 INFORMS’ Annual Conference, Philadelphia, PA.

FUSE Award #: 15-SP278

Page updated

Google Sites

Report abuse