Physical Sciences and Mathematics Commons^™

Cleaning Data Helps Clean The Air, Kelley Donalds, Xiangrong Liu

Management Faculty Publications

In this project, students use a real-world, complex database and experience firsthand the consequences of inadequate data modeling. The U.S. Environmental Protection Agency created the database as part of a multimillion dollar data collection effort undertaken in order to set limits on air pollutants from electric power plants. First, students explore the database to identify design limitations from the perspective of a data analyst with a specific goal. Second, students create a new database design which overcomes identified problems. Through this case study, students develop the skill to infer usage implications by studying the design of an existing database. This …

Assessing Satellite Image Data Fusion With Information Theory Metrics, James Cross

Dissertations and Theses

A common problem in remote sensing is estimating an image with high spatial and high spectral resolution given separate sources of measurements from satellite instruments, one having each of these desirable properties. This thesis presents a survey of seven families of algorithms which have been developed to provide this common pattern of satellite image data fusion. They are all tested on artificially degraded sets of satellite data from the Moderate Resolution Imaging Spectroradiometer (“MODIS”) with known ideal results, and evaluated using the commonly accepted data fusion assessment metrics spectral angle mapper (“SAM”) and Erreur Relative Globale Adimensionelle de Synth`ese (“ERGAS”). …

Essays On The Digital Divide, Belal Abdelfattah

Open Access Theses & Dissertations

The digital divide is a phenomenon that is globally persistent, despite rapidly decreasing costs in technology. While much of the variance in the adoption and use of information communication technology (ICT) that defines the digital divide can be explained by socioeconomic and demographic variables, there is still significant unaccounted variance that needs to be explained if the world's population is expected to be brought more fully into the digital age. The present research addresses this need with three cross-country studies. Study 1 primarily investigates the time individuals spend with traditional media sources as a likely explanation for their frequency of …

Three Essays On Social/Political Structures And Icts Use, Seungeui Ryu

Open Access Theses & Dissertations

My research identifies how social structures affect the use of the Internet and/or a mobile chat application and how the Internet impacts the political structure of a nation. In my first essay of the 3-essay Dissertation, I am designing three models based on social structure theory that are used to study the Internet and a popular mobile chat application's use by managers in South Korea, with the help of a survey instrument. In my first essay, the contribution is on i) testing a model of manager's personal behavior on Information and Communication Technology (ICT) use at the individual level involving …

Exploring Customer Specific Kpi Selection Strategies For An Adaptive Time Critical User Interface, Ingo Keck, Robert J. Ross

Conference papers

Rapid growth in the number of measures available to describe customer-organization relationships has presented a serious challenge for Business Intelligence (BI) interface developers as they attempt to provide business users with key customer information without requiring users to painstakingly sift through many interface windows and layers. In this paper we introduce a prototype Intelligent User Interface that we have deployed to partially address this issue. The interface builds on machine learning techniques to construct a ranking model of Key Performance Indicators (KPIs) that are used to select and present the most important customer metrics that can be made available to …

What Information About Cardiovascular Diseases Do People Search Online?, Ashutosh Sopan Jadhav, Stephen Wu, Amit P. Sheth, Jyotishman Pathak

Kno.e.sis Publications

The objective of this study is to understand the types of health information (health topics) that users search online for Cardiovascular Diseases, by performing categorization of health search queries (from Mayoclinic.com) using UMLS MetaMap based on UMLS concepts and semantic types.

Alignment And Dataset Identification Of Linked Data In Semantic Web, Kalpa Gunaratna, Sarasi Lalithsena, Amit P. Sheth

Kno.e.sis Publications

The Linked Open Data (LOD) cloud has gained significant attention in the Semantic Web community over the past few years. With rapid expansion in size and diversity, it consists of over 800 interlinked datasets with over 60 billion triples. These datasets encapsulate structured data and knowledge spanning over varied domains such as entertainment, life sciences, publications, geography, and government. Applications can take advantage of this by using the knowledge distributed over the interconnected datasets, which is not realistic to find in a single place elsewhere. However, two of the key obstacles in using the LOD cloud are the limited support …

Location Prediction Of Twitter Users Using Wikipedia, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan

Kno.e.sis Publications

The mining of user generated content in social media has proven very effective in domains ranging from personalization and recommendation systems to crisis management. The knowledge of online users locations makes their tweets more informative and adds another dimension to their analysis. Existing approaches to predict the location of Twitter users are purely data-driven and require large training data sets of geo-tagged tweets. The collection and modelling process of tweets can be time intensive. To overcome this drawback, we propose a novel knowledge based approach that does not require any training data. Our approach uses information in Wikipedia, about cities …

Refining Computerized Physician Order Entry Initiatives In An Adult Intensive Care Unit, Chevita Fuller

Walden Dissertations and Doctoral Studies

Computerized physician order entry (CPOE) is used in healthcare organizations to improve workflow processes and transcription, as well as to prevent prescribing errors. Previous research has indicated challenges associated with CPOE for end-users that predispose patients to unsafe practices. Unsafe CPOE practices can be detrimental within the intensive care unit (ICU) setting due to the complexity of nursing care. Consequently, end-user satisfaction and understanding of CPOE and electronic health record (EHR) functionality are vital to avoid error omissions. CPOE initiatives should be refined post system implementation to improve clinical workflow, medication processes, and end-user satisfaction. The purpose of this quality …

Evolutionary Algorithm Based Approach For Modeling Autonomously Trading Agents, Anil Yaman, Stephen Lucci, Izidor Gertner

Publications and Research

The autonomously trading agents described in this paper produce a decision to act such as: buy, sell or hold, based on the input data. In this work, we have simulated autonomously trading agents using the Echo State Network (ESNs) model. We generate a collection of trading agents that use different trading strategies using Evolutionary Programming (EP). The agents are tested on EUR/ USD real market data. The main goal of this study is to test the overall performance of this collection of agents when they are active simultaneously. Simulation results show that using different agents concurrently outperform a single agent …

Governing Knowledge Commons -- Introduction & Chapter 1, Brett M. Frischmann, Michael J. Madison, Katherine J. Strandburg

Book Chapters

“Knowledge commons” describes the institutionalized community governance of the sharing and, in some cases, creation, of information, science, knowledge, data, and other types of intellectual and cultural resources. It is the subject of enormous recent interest and enthusiasm with respect to policymaking about innovation, creative production, and intellectual property. Taking that enthusiasm as its starting point, Governing Knowledge Commons argues that policymaking should be based on evidence and a deeper understanding of what makes commons institutions work. It offers a systematic way to study knowledge commons, borrowing and building on Elinor Ostrom’s Nobel Prize-winning research on natural resource commons. It …

Commons At The Intersection Of Peer Production, Citizen Science, And Big Data: Galaxy Zoo, Michael J. Madison

Book Chapters

The knowledge commons research framework is applied to a case of commons governance grounded in research in modern astronomy. The case, Galaxy Zoo, is a leading example of at least three different contemporary phenomena. In the first place Galaxy Zoo is a global citizen science project, in which volunteer non-scientists have been recruited to participate in large-scale data analysis via the Internet. In the second place Galaxy Zoo is a highly successful example of peer production, sometimes known colloquially as crowdsourcing, by which data are gathered, supplied, and/or analyzed by very large numbers of anonymous and pseudonymous contributors to an …

Design And Implementation Of E-Commerce Site For Online Shopping, Sidhartha Reddy Vatrapu

All Capstone Projects

In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.

Online Shopping is a lifestyle e-commerce web application, which retails various fashion and lifestyle products (Currently Men’s Wear). This project allows viewing various products available enables registered users to purchase desired products instantly using PayPal payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to …

Neuroevolution And An Application Of An Agent Based Model For Financial Market, Anil Yaman

Dissertations and Theses

Market prediction is one of the most difficult problems for the machine learning community. Even though, successful trading strategies can be found for the training data using various optimization methods, these strategies usually do not perform well on the test data as expected. Therefore, selection of the correct strategy becomes problematic. In this study, we propose an evolutionary algorithm that produces a variation of trader agents ensuring that the trading strategies they use are different. We discuss that because the selection of the correct strategy is difficult, a variety of agents can be used simultaneously in order to reduce risk. …

Geospatial Data Pre-Processing On Watershed Datasets: A Gis Approach, Sreedhar Nallan, Leisa Armstrong, Barry Croke, Amiya K. Tripathy

Research outputs 2014 to 2021

Spatial data mining helps to identify interesting patterns from the spatial data sets. However, geo spatial data requires substantial data pre-processing before data can be interrogated further using data mining techniques. Multi-dimensional spatial data has been used to explain the spatial analysis and SOLAP for pre-processing data. This paper examines some of the methods for pre-processing of the data using Arc GIS 10.2 and Spatial Analyst with a case study dataset of a watershed.

Decision Support System Data For Farmer Decision Making, Pornchai Taechatanasat, Leisa Armstrong

Research outputs 2014 to 2021

The capacity of farmers and agricultural scientists to be able to make in-season decisions is dependent on accurate climate, soil and plant data. This paper will provide a review of the types of environmental and crop data that can be collected by sensors which can used for decision support systems (DSS) or be further interrogated for real time data mining and analysis. This paper also presents a review of the data requirements for agricultural decision making by firstly reviewing decision support frameworks and agricultural DSSs, data acquisition, sensors for data acquisition and examples of data incorporation for agricultural DSSs.

Mini-Track Introduction: Information Economics, Competition, Regulation, Law And Society, Eric K. Clemons, Robert John Kauffman, Thomas A. Weber

Research Collection School Of Computing and Information Systems

This mini-track is informed by the most modern thinking in information economics and competitive strategy, and includes many interdisciplinary applications of IS and technology.

Trustworthiness Of Web Services, Britto N. Arockiasamy

UNF Graduate Theses and Dissertations

Workflow systems orchestrate various business tasks to attain an objective. Web services can be leveraged to handle individual tasks. Before anyone intends to leverage service components, it is imperative and essential to evaluate the trustworthiness of these services. Therefore, choosing a trustworthy service has become an important decision while designing a workflow system. Trustworthiness can be defined as the likelihood of a service functioning as it is intended.

Selection of a service that satisfies business goals involves collecting relevant information such as security mechanisms, reliability, performance and availability. It is important to arrive at total trustworthiness, which incorporates all of …

A Hybrid Approach To Music Recommendation: Exploiting Collaborative Music Tags And Acoustic Features, Jaime C. Kaufman

UNF Graduate Theses and Dissertations

Recommendation systems make it easier for an individual to navigate through large datasets by recommending information relevant to the user. Companies such as Facebook, LinkedIn, Twitter, Netflix, Amazon, Pandora, and others utilize these types of systems in order to increase revenue by providing personalized recommendations. Recommendation systems generally use one of the two techniques: collaborative filtering (i.e., collective intelligence) and content-based filtering.

Systems using collaborative filtering recommend items based on a community of users, their preferences, and their browsing or shopping behavior. Examples include Netflix, Amazon shopping, and Last.fm. This approach has been proven effective due to increased popularity, and …

Wenzher: Comprehensive Vertical Search For Healthcare Domain, Liqiang Nie, Tao Li, Mohammad Akbari, Jialie Shen, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Online health seeking has transformed the way of health knowledge exchange and reusability. The existing general and vertical health search engines, however, just routinely return lists of matched documents or question answer (QA) pairs, which may overwhelm the seekers or not sufficiently meet the seekers’ expectations. Instead, our multilingual system is able to return one multi-faceted answer that is well-structured and precisely extracted from multiple heterogeneous healthcare sources. Further, should the seekers not be satisfied with the returned search results, our system can automatically route the unsolved questions to the professionals with relevant expertise

Coupling Graphs, Efficient Algorithms And B-Cell Epitope Prediction, Liang Zhao, Steven C. H. Hoi, Zhenhua Li, Limsoon Wong, Hung Nguyen

Research Collection School Of Computing and Information Systems

Coupling graphs are newly introduced in this paper to meet many application needs particularly in the field of bioinformatics. A coupling graph is a two-layer graph complex, in which each node from one layer of the graph complex has at least one connection with the nodes in the other layer, and vice versa. The coupling graph model is sufficiently powerful to capture strong and inherent associations between subgraph pairs in complicated applications. The focus of this paper is on mining algorithms of frequent coupling subgraphs and bioinformatics application. Although existing frequent subgraph mining algorithms are competent to identify frequent subgraphs …

Public Social Network Sites And Social Recruiting, Abby Peters

Open Access Theses & Dissertations

Social network sites (SNSs) are an increasingly popular form of social media used by individuals and organizations. As these platforms continue to transform the way people communicate with one another, they are simultaneously revolutionizing the way individuals interact with organizations. Part of this dramatic change is apparent in the processes by which organizations are recruiting employees and job seekers are pursuing employment. To investigate these phenomena, I employed the diffusion of innovations theory in a SNS context to examine the relationship between organizations' use of their corporate career website and their use of SNSs as recruiting sources. Subsequently, I used …

Loki: A Privacy-Conscious Platform For Crowdsourced Surveys, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Boreli

Research Collection School Of Computing and Information Systems

Emerging platforms such as Amazon Mechanical Turk and Google Consumer Surveys are increasingly being used by researchers and market analysts to crowdsource large-scale survey data from on-line populations at extremely low-cost. However, by participating in successive surveys, users risk being profiled and targeted, both by surveyors and by the platform itself. In this paper we propose, develop, and evaluate the design of a crowdsourcing platform, called Loki, that is privacy conscious. Our contributions are three-fold: (a) We propose Loki, a system that allows users to obfuscate their (ratings-based or multiple-choice) responses at-source based on their chosen privacy level, and gives …

An Investigation Of The User Satisfaction Of Customer Relationship Management Program, Sangeun Lee

Senior Honors Theses and Projects

The thesis investigates user satisfaction for Microsoft Dynamics CRM 2011 by conduction surveys to graduate level students. The training manual was developed to guide the way to follow instructions to create an order and an invoice.

A Scalable Backward Chaining-Based Reasoner For A Semantic Web, Hui Shi, Kurt Maly, Steven Zeil

Computer Science Faculty Publications

In this paper we consider knowledge bases that organize information using ontologies. Specifically, we investigate reasoning over a semantic web where the underlying knowledge base covers linked data about science research that are being harvested from the Web and are supplemented and edited by community members. In the semantic web over which we want to reason, frequent changes occur in the underlying knowledge base, and less frequent changes occur in the underlying ontology or the rule set that governs the reasoning. Interposing a backward chaining reasoner between a knowledge base and a query manager yields an architecture that can support …

Inferring The Untold: Mining Software Engineering Research Publication Networks, Santonu Sarkar, Subhajit Datta

Research Collection School Of Computing and Information Systems

Since the inception of organized research publication in software engineering in 1975, the discipline has gained maturity. This journey has been guided by the synergy of ideas and interactions of individuals. In this paper, we discuss a method for aggregating the corpus of 19,000+ papers and 21,000+ authors across 16 specialized software engineering venues. We focus on the approach of data collection, processing and storage. It can be used to address questions by the software engineering research community. We evaluate three questions: patterns of research topics with time, factors influencing the contribution of individual researchers, and the interaction among the …

Detecting Click Fraud In Online Advertising: A Data Mining Approach, Richard Oentaryo, Ee Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng-Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Kasun Perera, Bijay Neupane, Mustafa Faisal, Zeyar Aung, Wei Lee Woon, Wei Chen, Dhaval Patel, Daniel Berrar

Research Collection School Of Computing and Information Systems

Click fraud - the deliberate clicking on advertisements with no real interest on the product or service offered - is one of the most daunting problems in online advertising. Building an elective fraud detection method is thus pivotal for online advertising businesses. We organized a Fraud Detection in Mobile Advertising (FDMA) 2012 Competition, opening the opportunity for participants to work on real-world fraud data from BuzzCity Pte. Ltd., a global mobile advertising company based in Singapore. In particular, the task is to identify fraudulent publishers who generate illegitimate clicks, and distinguish them from normal publishers. The competition was held from …

Online Portfolio Selection: A Survey, Bin Li, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Online portfolio selection is a fundamental problem in computational finance, which has been extensively studied across several research communities, including finance, statistics, artificial intelligence, machine learning, and data mining. This article aims to provide a comprehensive survey and a structural understanding of online portfolio selection techniques published in the literature. From an online machine learning perspective, we first formulate online portfolio selection as a sequential decision problem, and then we survey a variety of state-of-the-art approaches, which are grouped into several major categories, including benchmarks, Follow-the-Winner approaches, Follow-the-Loser approaches, Pattern-Matching--based approaches, and Meta-Learning Algorithms. In addition to the problem formulation …

An Exploratory Analysis Of Twitter Keyword-Hashtag Networks And Knowledge Discovery Applications, Ahmed A. Hamed

Graduate College Dissertations and Theses

The emergence of social media has impacted the way people think, communicate, behave, learn, and conduct research. In recent years, a large number of studies have analyzed and modeled this social phenomena. Driven by commercial and social interests, social media has become an attractive subject for researchers. Accordingly, new models, algorithms, and applications to address specific domains and solve distinct problems have erupted. In this thesis, we propose a novel network model and a path mining algorithm called HashnetMiner to discover implicit knowledge that is not easily exposed using other network models. Our experiments using HashnetMiner have demonstrated anecdotal evidence …

Polymorphic Data Modeling, Steven R. Benson

Electronic Theses and Dissertations

There are currently no data modeling standards for modeling NoSQL document store databases. This work proposes a standard to fill the void. The proposed standard is based on our new data modeling pattern named The Polymorphic Table Pattern. The pattern embraces the “schemaless” nature of document store NoSQL while allowing the data modeler to use his or her existing skillsets. The concepts of our proposed modeling have been demonstrated against MongoDB.