Databases and Information Systems Commons^™

Testing Data Vault-Based Data Warehouse, Connard N. Williams

College of Graduate Studies: Theses & Dissertations

Data warehouse (DW) projects are undertakings that require integration of disparate sources of data, a well-defined mapping of the source data to the reconciled data, and effective Extract, Transform, and Load (ETL) processes. Owing to the complexity of data warehouse projects, great emphasis must be placed on an agile-based approach with properly developed and executed test plans throughout the various stages of designing, developing, and implementing the data warehouse to mitigate against budget overruns, missed deadlines, low customer satisfaction, and outright project failures. Yet, there are often attempts to test the data warehouse exactly like traditional back-end databases and legacy …

Exploring Strategies For Retaining Information Technology Professionals: A Case Study, Shannon J. Thomas

Walden Dissertations and Doctoral Studies

In the 21st century, retaining information technology (IT) professionals is critical to a company's productivity and overall success. Senior IT leaders need effective strategies to retain skilled IT professionals. Guided by the general systems theory and the transformational leadership theory, the purpose of this qualitative exploratory case study was to explore the retention strategies used by 2 senior IT leaders in Atlanta, Georgia to retain IT professionals. Semistructured interviews were employed to elicit detailed narratives from these IT leaders on their experiences in retaining IT professionals. A review of company documents, as well as member-checking of initial interview transcripts, helped …

Communication Constructs That Influence Information Technology Project Failure, Vanessa Lajuan Ruth Mackey

Walden Dissertations and Doctoral Studies

Ineffective communication behavioral constructs in the workplace that lead to information technology (IT) project failure and in some cases organization failure are increasingly becoming a management concern. Despite this trend, there is little research on the communication behavioral constructs that contribute to IT project failure rates. The purpose of this phenomenological study was to explore the lived experiences of business analysts, programmers, and programmer analysts pertaining to the behavioral constructs associated with effective and ineffective communication. The research questions addressed these behaviors from a conceptual framework based on communication theory, organizational information processing theory, and critical social theory. This framework …

Relational Agency, Networked Technology, And The Social Media Aftermath Of The Boston Marathon Bombing, Megan M. Mcintyre

USF Tampa Graduate Theses and Dissertations

Agency is a foundational and ongoing concern for the field of Rhetoric and Composition. Long thought to be a product and possession of human action, rhetorical agency represents the most obvious connection between the educational and theoretical work of the field and the civic project of liberal arts and humanities education. Existing theories of anthropocentric rhetorical agency are insufficient, however, to account for the complex technological work of digitally enmeshed networks of humans and nonhumans. To better account for these complex networks, this project argues for the introduction of new materialist theories of distributed agency into conversations about agency within …

Push, Pull, And Spill: A Transdisciplinary Case Study In Municipal Open Government, Jan Whittington, Ryan Calo, Mike Simon, Jesse Woo, Meg Young, Perter Schmiedeskamp

Articles

Municipal open data raises hopes and concerns. The activities of cities produce a wide array of data, data that is vastly enriched by ubiquitous computing. Municipal data is opened as it is pushed to, pulled by, and spilled to the public through online portals, requests for public records, and releases by cities and their vendors, contractors, and partners. By opening data, cities hope to raise public trust and prompt innovation. Municipal data, however, is often about the people who live, work, and travel in the city. By opening data, cities raise concern for privacy and social justice.

This article presents …

A Comparison Of Cloud Computing Database Security Algorithms, Joseph A. Hoeppner

UNF Graduate Theses and Dissertations

The cloud database is a relatively new type of distributed database that allows companies and individuals to purchase computing time and memory from a vendor. This allows a user to only pay for the resources they use, which saves them both time and money. While the cloud in general can solve problems that have previously been too costly or time-intensive, it also opens the door to new security problems because of its distributed nature. Several approaches have been proposed to increase the security of cloud databases, though each seems to fall short in one area or another.

This thesis presents …

Profiling Web Archives For Efficient Memento Query Routing, Sawood Alam, Michael L. Nelson, Herbert Van De Sompel, Lyudmila L. Balakireva, Harihar Shankar, David S. H. Rosenthal

Computer Science Faculty Publications

No abstract provided.

Push Or Pull? A Website's Strategic Choice Of Content Delivery Mechanism, Dan Ma

Research Collection School Of Computing and Information Systems

Really simple syndication (RSS) technology enables an alternative delivery mechanism for online content. Instead of waiting passively for users to pull online content out, websites can push it to potential users through RSS. This is expected to significantly affect user behavior, website profitability, and market equilibrium. This research uses an economic model to study the impact of RSS adoption and examine whether it increases a website’s profit and competitive advantage. The findings are intriguing: they demonstrate that RSS can either increase or decrease website profit. In a competitive context, RSS adoption can actually be a disadvantage; in some cases, it …

Special Section: Economics, Electronic Commerce, And Competitive Strategy, Eric K. Clemons, Rajiv M. Dewan, Robert John Kauffman

Research Collection School Of Computing and Information Systems

The title of this year;s special section of selected papers, whose initial versionswere presented at the “Economics and Electronic Commerce,” and “Information Technologyand Competitive Strategy” mini-tracks of the 2001 Hawaii International Conferenceon Systems Science (HICSS), reflects the increasing convergence of ideas fromEconomics and Information Systems (IS) research. This convergence has been occurringover the last several years and is related to the developments in e-commerce. ISresearch has been rapidly coming of age, driven by the ever-increasing importance ofinformation technology (IT) in the marketplace, and the need for managers, investors,policy-makers, and the public to understand how to more effectively navigate in ourhighly …

Community Discovery From Social Media By Low-Rank Matrix Recovery, Jinfeng Zhuang, Mei Tao, Steven C. H. Hoi, Xian-Sheng Hua, Yongdong Zhang

Research Collection School Of Computing and Information Systems

The pervasive usage and reach of social media have attracted a surge of attention in the multimedia research community. Community discovery from social media has therefore become an important yet challenging issue. However, due to the subjective generating process, the explicitly observed communities (e.g., group-user and user-user relationship) are often noisy and incomplete in nature. This paper presents a novel approach to discovering communities from social media, including the group membership and user friend structure, by exploring a low-rank matrix recovery technique. In particular, we take Flickr as one exemplary social media platform. We first model the observed indicator matrix …

An Adaptive Gradient Method For Online Auc Maximization, Yi Ding, Peilin Zhao, Steven C. H. Hoi, Yew-Soon Ong

Research Collection School Of Computing and Information Systems

Learning for maximizing AUC performance is an important research problem in machine learning. Unlike traditional batch learning methods for maximizing AUC which often suffer from poor scalability, recent years have witnessed some emerging studies that attempt to maximize AUC by single-pass online learning approaches. Despite their encouraging results reported, the existing online AUC maximization algorithms often adopt simple stochastic gradient descent approaches, which fail to exploit the geometry knowledge of the data observed in the online learning process, and thus could suffer from relatively slow convergence. To overcome the limitation of the existing studies, in this paper, we propose a …

Are Features Equally Representative? A Feature-Centric Recommendation, Chenyi Zhang, Ke Wang, Ee-Peng Lim, Qinneng Xu, Jianling Sun, Hongkun Yu

Research Collection School Of Computing and Information Systems

Typically a user prefers an item (e.g., a movie) because she likes certain features of the item (e.g., director, genre, producer). This observation motivates us to consider a feature-centric recommendation approach to item recommendation: instead of directly predicting the rating on items, we predict the rating on the features of items, and use such ratings to derive the rating on an item. This approach offers several advantages over the traditional item-centric approach: it incorporates more information about why a user chooses an item, it generalizes better due to the denser feature rating data, it explains the prediction of item ratings …

Saliency-Guided Color-To-Gray Conversion Using Region-Based Optimization, Hao Du, Shengfeng He, Bin Sheng, Lizhuang Ma, Rynson W.H. Lau

Research Collection School Of Computing and Information Systems

Image decolorization is a fundamental problem for many real-world applications, including monochrome printing and photograph rendering. In this paper, we propose a new color-to-gray conversion method that is based on a region-based saliency model. First, we construct a parametric color-to-gray mapping function based on global color information as well as local contrast. Second, we propose a region-based saliency model that computes visual contrast among pixel regions. Third, we minimize the salience difference between the original color image and the output grayscale image in order to preserve contrast discrimination. To evaluate the performance of the proposed method in preserving contrast in …

Modeling Neuromorphic Persistent Firing Networks, Ning Ning, Guoqi Li, Wei He, Kejie Huang, Li Pan, Kiruthika Ramanathan, Rong Zhao, Luping Shi

Research Collection School Of Computing and Information Systems

Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon …

Time Series Similarity Search In Distributed Key-Value Data Stores Using R-Trees, Aleksey Charapko

UNF Graduate Theses and Dissertations

Time series data are sequences of data points collected at certain time intervals. The advance in mobile and sensor technologies has led to rapid growth in the available amount of time series data. The ability to search large time series data sets can be extremely useful in many applications. In healthcare, a system monitoring vital signals can perform a search against the past data and identify possible health threatening conditions. In engineering, a system can analyze performances of complicated equipment and identify possible failure situations or needs of maintenance based on historical data.

Existing search methods for time series data …