Physical Sciences and Mathematics Commons^™

Reputation-Aware Trajectory-Based Data Mining In The Internet Of Things (Iot), Samia Tasnim

FIU Electronic Theses and Dissertations

Internet of Things (IoT) is a critically important technology for the acquisition of spatiotemporally dense data in diverse applications, ranging from environmental monitoring to surveillance systems. Such data helps us improve our transportation systems, monitor our air quality and the spread of diseases, respond to natural disasters, and a bevy of other applications. However, IoT sensor data is error-prone due to a number of reasons: sensors may be deployed in hazardous environments, may deplete their energy resources, have mechanical faults, or maybe become the targets of malicious attacks by adversaries. While previous research has attempted to improve the quality of …

Learnfca: A Fuzzy Fca And Probability Based Approach For Learning And Classification, Suraj Ketan Samal

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Formal concept analysis(FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. Over the past several years, many of its extensions have been proposed and applied in several domains including data mining, machine learning, knowledge management, semantic web, software development, chemistry ,biology, medicine, data analytics, biology and ontology engineering.

This thesis reviews the state-of-the-art of theory of Formal Concept Analysis(FCA) and its various extensions that have been developed and well-studied in the past several years. We discuss their historical roots, reproduce the original definitions and derivations with illustrative examples. Further, we provide …

Promotional Campaigns In The Era Of Social Platforms, Noor E. Abu-El-Rub

Computer Science ETDs

The rise of social media has facilitated the diffusion of information to more easily reach millions of users. While some users connect with friends and organically share information and opinions on social media, others have exploited these platforms to gain influence and profit through promotional campaigns and advertising. The existence of promotional campaigns contributes to the spread of misleading information, spam, and fake news. Thus, these campaigns affect the trustworthiness and reliability of social media and render it as a crowd advertising platform. This dissertation studies the existence of promotional campaigns in social media and explores different ways users and …

Supervised Machine Learning Models For Fake News Detection, Andrea Lopez, Adelo Vieira, Zafar Ahsan, Farooq Sabib, Shirley Marinho

ICT

Fake news or the distribution of disinformation has become one of the most challenging issues in society. News and information are churned out across online websites and platforms in real-time, with little or no way for the viewing public to determine what is real or manufactured. But an awareness of what we are consuming online is becoming apparent and efforts are underway to explore how we separate fake content from genuine and truthful information. The most challenging part of fake news is determining how to spot it. In technology, there are ways to help us do this. Supervised machine learning …

Data Mining Techniques For Predicting Real Estate Trends, David Vargason

Mathematics and Computer Science Capstones

A wide variety of businesses and government agencies support the U.S. real estate market. Examples would include sales agents, national lenders, local credit unions, private mortgage and title insurers, and government sponsored entities (Freddie Mac and Fannie Mae), to name a few. The financial performance and overall success of these organizations depends in large part on the health of the overall real estate market. According to the National Association of Home Builders (NAHB), the construction of one single-family home of average size creates the equivalent of nearly 3 new jobs for a year (Greiner, 2015). The economic impact is significant, …

Commonsense Knowledge In Sentiment Analysis Of Ordinance Reactions For Smart Governance, Manish Puri

Theses, Dissertations and Culminating Projects

Smart Governance is an emerging research area which has attracted scientific as well as policy interests, and aims to improve collaboration between government and citizens, as well as other stakeholders. Our project aims to enable lawmakers to incorporate data driven decision making in enacting ordinances. Our first objective is to create a mechanism for mapping ordinances (local laws) and tweets to Smart City Characteristics (SCC). The use of SCC has allowed us to create a mapping between a huge number of ordinances and tweets, and the use of Commonsense Knowledge (CSK) has allowed us to utilize human judgment in mapping. …

Supervised Machine Learning Models For Fake News Detection, Gofaas Group, Andrea Lopez, Adelo Vieira, Zafar Ahsan, Farooq Saqib, Shirley Marinho

ICT

Fake news or the distribution of disinformation has become one of the most challenging issues in society. News and information are churned out across online websites and platforms in real-time, with little or no way for the viewing public to determine what is real or manufactured. But an awareness of what we are consuming online is becoming apparent and efforts are underway to explore how we separate fake content from genuine and truthful information.

The most challenging part of fake news is determining how to spot it. In technology, there are ways to help us do this. Supervised machine learning …

Econometrics In R Program, Ian Connors

Senior Honors Projects

Econometrics and Datamining using R Programming

I provide an analysis of Rhode Island economic conditions by comparing economic variables in the state to other states in New England and the country as a whole. I learned the programming language R to complete the analysis using published economic statistics. Statistics provided from the Bureau of Economic Analysis (BEA) show quarterly or annual trends which can assist the researcher in predicting future trends. This data includes figures such as real personal income, real GDP, per capita real GDP, regional price parities, housing prices, and total full-time and part-time employment by state; additionally, …

Analyzing And Estimating Cyberattack Trends By Performing Data Mining On A Cybersecurity Data Set, Chan Young Koh

Honors Program Theses and Projects

More than five billion personal information has been compromised over the past eight years through data breaches from notable companies, and the damage related to cybercrime is expected to reach six trillion USD annually by the year of 2021. Interestingly, recent cyberattacks were aimed specifically at credit agencies and companies that hold credit information of their customers and employees. The question is: “Why is it difficult to protect against or evade cyberattacks even for these prestigious companies?”. The purpose of this research is to bring the notion of notorious, rapidly-multiplying cyberthreats. Hence, the research focuses on analyzing cyberattack techniques and …

Intelligent Malware Detection Using File-To-File Relations And Enhancing Its Security Against Adversarial Attacks, Lingwei Chen

Graduate Theses, Dissertations, and Problem Reports

With computing devices and the Internet being indispensable in people's everyday life, malware has posed serious threats to their security, making its detection of utmost concern. To protect legitimate users from the evolving malware attacks, machine learning-based systems have been successfully deployed and offer unparalleled flexibility in automatic malware detection. In most of these systems, resting on the analysis of different content-based features either statically or dynamically extracted from the file samples, various kinds of classifiers are constructed to detect malware. However, besides content-based features, file-to-file relations, such as file co-existence, can provide valuable information in malware detection and make …

The Political Power Of Twitter, James Usher, Pierpaolo Dondio, Lucia Morales

Conference papers

In June 2016, the British voted by 52 per cent to leave the EU, a club the UK joined in 1973. This paper examines Twitter public and political party discourse surrounding the BREXIT withdrawal agreement. In particular, we focus on tweets from four different BREXIT exit strategies known as “Norway”, “Article 50”, the “Backstop” and “No Deal” and their effect on the pound and FTSE 100 index from the period of December 10th 2018 to February 24th 2019. Our approach focuses on using a Naive Bayes classification algorithm to assess political party and public Twitter sentiment. A Granger causality analysis …

Indirect Relatedness, Evaluation, And Visualization For Literature Based Discovery, Sam Henry

Theses and Dissertations

The exponential growth of scientific literature is creating an increased need for systems to process and assimilate knowledge contained within text. Literature Based Discovery (LBD) is a well established field that seeks to synthesize new knowledge from existing literature, but it has remained primarily in the theoretical realm rather than in real-world application. This lack of real-world adoption is due in part to the difficulty of LBD, but also due to several solvable problems present in LBD today. Of these problems, the ones in most critical need of improvement are: (1) the over-generation of knowledge by LBD systems, (2) a …