Databases and Information Systems Commons^™

Diffusion Of Falsehoods On Social Media, Kelvin Kizito King

Theses and Dissertations

Misinformation has captured the interest of academia in recent years with several studies looking at the topic broadly. However, these studies mostly focused on rumors which are social in nature and can be either classified as false or real. In this research, we attempt to bridge the gap in the literature by examining the impacts of user characteristics and feature contents on the diffusion of (mis)information using verified true and false information. We apply a topic allocation model augmented by both supervised and unsupervised machine learning algorithms to identify tweets on novel topics. We find that retweet count is higher …

Creativity And Engagement In Ideas Crowdsourcing: A Situation Awareness Perspective, James Gitau Wairimu

Theses and Dissertations

This dissertation investigates the influence of performance feedback in user motivation and creativity development in idea crowdsourcing engagement. Creativity occurs when users of idea crowdsourcing communities engage in direct and indirect interactions that expose them to a pool of knowledge that enhances their cognitive development leading to the contribution of novel ideas for innovation in organizations. Additionally, participant motivation to engage in ideas crowdsourcing is increased through rewards and conditions that make the ideation process more inclusive and enjoyable. An idea network design is developed by applying social network analysis principles. The idea network design consists of mechanisms for motivating …

An Investigation Into The Optimal Use Of Frequency-Based Weights To Improve The Performance Of Entity Resolution, Bingyi Zhong

Theses and Dissertations

Using a weight-based match score has been studied as a way to improve the accuracy of record linking (entity resolution) since Fellegi and Sunter first described the idea of probabilistic agreement and disagreement weights in their seminal work “A Theory of Record Linking.” However, the original work only described weight associated with an entity attribute. Later researchers such as Herzog et al suggested the weighting scheme could be extended to apply to frequently-occurring attribute values (frequency-based weights) instead of just the attribute as in the Fellegi-Sunter scheme. However, there has been little definitive research as to how frequency-based weights should …

Improving Energy-Efficiency Through Smart Data Placement In Hadoop Clusters, Ahmed Mostafa

Theses and Dissertations

Hadoop, a pioneering open source framework, has revolutionized the big data world because of its ability to process vast amounts of unstructured and semi-structured data. This ability makes Hadoop the ‘go-to’ technology for many industries that generate big data, thus it also aids in being cost effective, unlike other legacy systems. Hadoop MapReduce is used in large scale data parallel applications to process massive amounts of data across a cluster and is used for scheduling, processing, and executing jobs. Basically, MapReduce is the right hand of Hadoop, as its library is needed to process these large data sets. In this …

Relational Database Design And Multi-Objective Database Queries For Position Navigation And Timing Data, Sean A. Mochocki

Theses and Dissertations

Performing flight tests is a natural part of researching cutting edge sensors and filters for sensor integration. Unfortunately, tests are expensive, and typically take many months of planning. A sensible goal would be to make previously collected data readily available to researchers for future development. The Air Force Institute of Technology (AFIT) has hundreds of data logs potentially available to aid in facilitating further research in the area of navigation. A database would provide a common location where older and newer data sets are available. Such a database must be able to store the sensor data, metadata about the sensors, …

Factors That Influence The Perception Of Higher Education Leaders In The Adoption Process Of Instructional Technology And Distance Education, Diego Tibaquirá

Theses and Dissertations

The problem addressed by this study was that many administrators at institutions of higher learning are faced with the task of finding ways to provide the latest technologies while being extremely constricted by budgets and the rising cost of education. The purpose of this study was to determine the factors that influence the perceptions of higher education leaders in the adoption process of Instructional Technology and Distance Education. This included an examination of the decision-making process and what determined if Instructional Technology and Distance Education were either implemented or upgraded at various higher learning institutions.

The researcher implemented a mixed-methods …

Multi-Resolution Models For Learning Multilevel Abstract Representation With Application To Information Retrieval, Tolgahan Cakaloglu

Theses and Dissertations

Deep language models learning a hierarchical representation proved to be a powerful tool for natural language processing, text mining, and information retrieval tasks. However, more specifically, representations that perform well for ad-hoc retrieval must capture semantic meaning at different levels of abstraction or context-scopes. The primary goal of ad-hoc retrieval is to find relevant documents satisfying the information need posted in a natural language query. It requires a good understanding of the query and all the documents in a corpus, which is difficult because the meaning of natural language texts depends on the context, syntax, and semantics. In this dissertation, …

Data Gathering In Cognitive Radio Ad Hoc And Sensor Wireless Networks, Kimberly A. Brown

Theses and Dissertations

Data gathering is a network communication task in which all of the network’s nodes send their individual messages to a distinguished sink node. In cognitive radio ad hoc and sensor wireless networks (CR-AHSWNs), unlicensed secondary users (SUs) opportunistically use channels when the licensed primary users are not using them. Therefore, the channels available to each SU vary with time and location, which makes the development of data gathering algorithms for CR-AHSWNs challenging.

In this thesis, a data gathering protocol for CR-AHSWNs is proposed. The protocol consists of several distributed SU action selection and channel selection algorithms. An algorithm that can …

Testing The Fault Tolerance Of A Wide Area Backup Protection System Using Spin, Kenneth James

Theses and Dissertations

Cyber-physical systems are increasingly prevalent in daily life. Smart grids in particular are becoming more interconnected and autonomously operated. Despite the advantages, new challenges arise in the form of defending these assets. Recent studies reveal that small-scale, coordinated cyber-attacks on only a few substations across the U.S. could result in cascading failures affecting the entire nation. In support of defending critical infrastructure, this thesis tests the fault tolerance of a backup protection system. Each transmission line in the system incorporates autonomous agents which monitor the status of the line and make decisions regarding the safety of the grid. Various malfunctions …

Evaluating Machine Learning Techniques For Smart Home Device Classification, Angelito E. Aragon Jr.

Theses and Dissertations

Smart devices in the Internet of Things (IoT) have transformed the management of personal and industrial spaces. Leveraging inexpensive computing, smart devices enable remote sensing and automated control over a diverse range of processes. Even as IoT devices provide numerous benefits, it is vital that their emerging security implications are studied. IoT device design typically focuses on cost efficiency and time to market, leading to limited built-in encryption, questionable supply chains, and poor data security. In a 2017 report, the United States Government Accountability Office recommended that the Department of Defense investigate the risks IoT devices pose to operations security, …

Imitating Human Responses Via A Dual-Process Model Approach, Matthew A. Grimm

Theses and Dissertations

Human-autonomous system teaming is becoming more prevalent in the Air Force and in society. Often, the concept of a shared mental model is discussed as a means to enhance collaborative work arrangements between a human and an autonomous system. The idea being that when the models are aligned, the team is more productive due to an increase in trust, predictability, and apparent understanding. This research presents the Dual-Process Model using multivariate normal probability density functions (DPM-MN), which is a cognitive architecture algorithm based on the psychological dual-process theory. The dual-process theory proposes a bipartite decision-making process in people. It labels …

Curtus: An Nlp Tool To Map Job Skills To Academic Courses, Daniel Rockwell

Theses and Dissertations

Many businesses are burdened with the need to train students for the job instead of finding them prepared for it. Few business leaders feel that colleges prepare students for future jobs from day one. It can be a challenge for colleges to determine if their curricula meet the industry needs. Mapping industry needs to academic courses can be advantageous to both parties as it will allow colleges to be aligned with the industry needs and accordingly satisfy those needs and will allow the industry to hire better prepared graduates. In an attempt to address this, a system prototype that uses …

Adapting Financial Technology Standards To Blockchain Platforms, Gabriel Bello

Theses and Dissertations

Traditional payment systems have standards designed to keep transaction data secure, but blockchain systems are not in scope for such security standards. We compare the Payment Application Data Security Standard’s (PA-DSS) applicability towards transaction-supported blockchain platforms to test the standard’s applicability. By highlighting the differences in implementation on traditional and decentralized transaction platforms, we critique and adapt the standards to fit the decentralized model. In two case studies, we analyze the QTUM and Ethereum blockchain platforms’ industry compliance, as their payment platforms support transactions equivalent to that of applications governed by the PA-DSS. We determine QTUM’s and Ethereum’s capabilities to …

Automated Essay Evaluation Using Natural Language Processing And Machine Learning, Harshanthi Ghanta

Theses and Dissertations

The goal of automated essay evaluation is to assign grades to essays and provide feedback using computers. Automated evaluation is increasingly being used in classrooms and online exams. The aim of this project is to develop machine learning models for performing automated essay scoring and evaluate their performance. In this research, a publicly available essay data set was used to train and test the efficacy of the adopted techniques. Natural language processing techniques were used to extract features from essays in the dataset. Three different existing machine learning algorithms were used on the chosen dataset. The data was divided into …

A Methodology For Evaluating Relational And Nosql Databases For Small-Scale Storage And Retrieval, Ryan D. Engle

Theses and Dissertations

Modern systems record large quantities of electronic data capturing time-ordered events, system state information, and behavior. Subsequent analysis enables historic and current system status reporting, supports fault investigations, and may provide insight for emerging system trends. Unfortunately, the management of log data requires ever more efficient and complex storage tools to access, manipulate, and retrieve these records. Truly effective solutions also require a well-planned architecture supporting the needs of multiple stakeholders. Historically, database requirements were well-served by relational data models, however modern, non-relational databases, i.e. NoSQL, solutions, initially intended for “big data” distributed system may also provide value for smaller-scale …

The Application Of Text Mining And Data Visualization Techniques To Textual Corpus Exploration, Jeffrey R. Smith Jr.

Theses and Dissertations

Unstructured data in the digital universe is growing rapidly and shows no evidence of slowing anytime soon. With the acceleration of growth in digital data being generated and stored on the World Wide Web, the prospect of information overload is much more prevalent now than it has been in the past. As a preemptive analytic measure, organizations across many industries have begun implementing text mining techniques to analyze such large sources of unstructured data. Utilizing various text mining techniques such as n -gram analysis, document and term frequency analysis, correlation analysis, and topic modeling methodologies, this research seeks to develop …

Developing A Cyberterrorism Policy: Incorporating Individual Values, Osama Bassam J. Rabie

Theses and Dissertations

Preventing cyberterrorism is becoming a necessity for individuals, organizations, and governments. However, current policies focus on technical and managerial aspects without asking for experts and non-experts values and preferences for preventing cyberterrorism. This study employs value focused thinking and public value forum to bare strategic measures and alternatives for complex policy decisions for preventing cyberterrorism. The strategic measures and alternatives are per socio-technical process.

A System For Stratified Sampling Of Entity Resolution Results To Assess And Improve Accuracy With Minimal Clerical Review Effort, Daniel L. Pullen

Theses and Dissertations

Organizations across many industries from banking to medicine depend on master data that describe their customers, products and services. Data integration and unique representations of master data are supported by Entity Resolution processes to link records for the same master entity. Master data is key to the core operations of these organizations. Unfortunately, many of these organizations do not use a systematic method, or in some cases, use no method for measuring and improving the quality of record linkage provided by Entity Resolution. This research presents an implementation and proposed methodology for routinely and systematically measuring the quality of Entity …

Stream Data Quality Assessment Based On Distributed Computing Platforms, Wei Dai

Theses and Dissertations

In this era of big data, data quality will be increasingly important because people need high quality data to make decisions, analyze patterns, and discover knowledge. So, measuring data quality is a vital mission. In this thesis, Chapter 1 is the introduction, Chapter 2 is a literature review, Chapter 3 illustrates how to discover potentially important data based on a reference algorithm, a frequency algorithm, and an entropy algorithm, in Chapter 4, the author offers a concise five-layer data quality framework to measure stream data quality scorecards, in Chapter 5, the author shows how to visualize data quality scorecards through …

Blocking Strategies For Performing Entity Resolution In A Distributed Computing Environment, Pei Wang

Theses and Dissertations

Entity resolution (ER) is an O(n2) problem where n is the number of records to be processed. The pair-wise nature of ER makes it impractical to perform on large datasets without the use of a technique called blocking. In blocking the records are separated into groups (called blocks) in such a way the records most likely to match are within the same block. The ER system only compares pairs of records within the same block, thus reducing the total number of pairs to match. Traditionally, blocking algorithms build inverted indices in memory to quickly locate potential matches. With the advent …

Inferred Error Rates For Entity Resolution, Melody Lynn Penning

Theses and Dissertations

This dissertation is focused on the methodology of determining the quality of the results of entity resolution. Entity resolution methodologies results in different success rates. Until now these success rates have been measured by counting all of the correctly and incorrectly matched results. This is quickly becoming an intractable task as datasets grow in size. In order to address this problem this research tests and describes the results of count based measures as compared with inferred measures borrowed from the information retrieval community. The key contribution of this research is a proof of concept in a controlled environment that demonstrates …

Women On The Board Of Directors And Their Impact On The Financial Performance Of A Firm: An Empirical Investigation Of Female Directors In The United States Technology Sector, Obinna Mogbogu

Theses and Dissertations

This study uses a sample of S&P 500 firms in the United States technology sector to investigate the likely relationship between female directors and financial performance of firms measured by return on average assets and return on average equity as the two accounting based measures of performance. Reasonable theoretical arguments drawn from resource dependency, human capital, agency, and social psychology theory, suggests that the gender diversity of the board of directors may have either a positive, negative, or neutral effect on the financial performance of the firm. Using nonparametric statistics approach, we find a small negative relationship between female directors …

A Framework For Collecting, Extracting And Managing Event Identity Information From Textual Content In Social Media, Debanjan Mahata

Theses and Dissertations

With the popularity of social media platforms such as Facebook, Twitter and Google Plus, there has been voluminous growth in the digital footprints of real-life events on the Internet. The user-generated colloquial and concise textual content related to different types of real-life events, available in these websites, acts as an extremely useful source for researchers and organizations for extracting valuable and insightful information. There has been significant improvement in natural language processing techniques for mining formal and long textual content commonly found in newspapers. It is still a challenging task to mine textual information from the social media channels producing …

Exploring Data Mining Techniques For Tree Species Classification Using Co-Registered Lidar And Hyperspectral Data, Julia K. Marrs

Theses and Dissertations

NASA Goddard’s LiDAR, Hyperspectral, and Thermal imager provides co-registered remote sensing data on experimental forests. Data mining methods were used to achieve a final tree species classification accuracy of 68% using a combined LiDAR and hyperspectral dataset, and show promise for addressing deforestation and carbon sequestration on a species-specific level.

Fuzzy Decision Tree-Based Inference System For Liver Disease Diagnosis, Himaja Sivaraju

Theses and Dissertations

Medical diagnosis can be challenging because of a number of factors. Uncertainty in the diagnosis process arises from inaccuracy in the measurement of patient attributes, missing attribute data and limitation in the medical expert’s ability to define cause and effect relationships when there are multiple interrelated variables. Given this situation, a decision support system, which can help doctors come up with a more reliable diagnosis, can have a lot of potential.

Decision trees are used in data mining for classification and regression. They are simple to understand and interpret as they can be visualized. But, one of the disadvantages of …

A Design For An Identity Resolution Service As An Extension Of The Entity Identity Information Management Model, Fumiko Kobayashi

Theses and Dissertations

This research describes the design of an identity resolution service (IRS), which provides extensions and enhancements to the current EIIM model. The IRS provides a set of application programming interfaces (API) which allow identity resolution (IR) to be performed interactively. Interactive IR is a logical extension to the existing EIIM model. It will separate the IR function from the EIIM batch update process. The new (IR) function: 1) Operates interactively 2) Has its own probabilistic matching rules defined separately from the identity rules used in the EIIM update process 3) Has the ability to return a confidence rating alongside a …

A System To Support Clerical Review, Correction, And Confirmation Assertions In Entity Identity Information Management, Cheng Chen

Theses and Dissertations

Clerical review of Entity Resolution(ER) is crucial for maintaining the entity identity integrity of an Entity Identity Information Management (EIIM) system. However, the clerical review process presents several problems. These problems include Entity Identity Structures (EIS) that are difficult to read and interpret, excessive time and effort to review large Identity Knowledgebase (IKB), and the duplication of effort in repeatedly reviewing the same EIS in same EIIM review cycle or across multiple review cycles. Although the original EIIM model envisioned and demonstrated the value of correction assertions, these are applied to correct errors after they have been found. The original …

Context-Sensitive Entity Resolution, William C. Decker

Theses and Dissertations

This dissertation proposes an entity resolution approach that is context-sensitive, meaning it relies less on high-risk information, such as social security numbers, to discern whether records from a data set belong to the same real-world individual or to different real-world individuals. The research follows an iterative process of assessing the quality, or fitness of use, of identity data housed in an educational institution and then processing the data with the proposed context-sensitive entity resolution (ER) rule set. The efficacy of this process is demonstrated through calculation of the four-year adjusted cohort graduation rate, a prevalent longitudinal data analysis challenge for …

Unknown Threat Detection With Honeypot Ensemble Analsyis Using Big Datasecurity Architecture, Michael Eugene Sanders

Theses and Dissertations

The amount of data that is being generated continues to rapidly grow in size and complexity. Frameworks such as Apache Hadoop and Apache Spark are evolving at a rapid rate as organizations are building data driven applications to gain competitive advantages. Data analytics frameworks decomposes our problems to build applications that are more than just inference and can help make predictions as well as prescriptions to problems in real time instead of batch processes.

Information Security is becoming more important to organizations as the Internet and cloud technologies become more integrated with their internal processes. The number of attacks and …

Using Software Defined Networking To Solve Missed Firewall Architecture In Legacy Networks, Jared Dean Vogel

Theses and Dissertations

This study is concerned with migrating traditional networks and their inherent firewall architecture to Software Defined Networking (SDN) architecture to provide an initial attempt at preventing application downtime due to hidden firewall domain rules. In legacy organization environments the networking engineers, firewall teams, and application analysts are often silo groups, but Software Defined Networking (SDN) can blur the lines between these group silos.

This thesis first outlines the interworking of SDN, traditional firewall architecture and how it interacts with SDN, an experiment of implementation, and the resulting conclusions.

Testing with SDN shows we are approaching new environments where the edges …