Databases and Information Systems Commons^™

Enhancing Brand Equity Through Flow And Telepresence: A Comparison Of 2d And 3d Virtual Worlds, Fiona Fui-Hoon Nah, B. Eschenbrenner, D. Dewester

Research Collection School Of Computing and Information Systems

This research uses theories of flow, telepresence, positive emotions, and brand equity to examine the effect of using two-dimensional versus three-dimensional virtual world environments on telepresence, enjoyment, brand equity, and behavioral intention. The findings suggest that the 3D virtual world environment produces both positive and negative effects on brand equity when compared to the 2D environment. The positive effect of the 3D virtual world environment on brand equity occurs through telepresence, a specific aspect of flow, as well as enjoyment. The negative effect on brand equity can be explained using distraction-conflict theory in which attentional conflicts faced by users of …

Information Quality On The World Wide Web: Development Of A Framework, J. Kandari, E. Jones, Fiona Fui-Hoon Nah, R. Bishu

Research Collection School Of Computing and Information Systems

Data consumers are provided with easy online access to information on the World Wide Web. However, consumers face information quality problems in their quest for information. This paper focuses on the development of an instrument to measure information quality (IQ) on the World Wide Web from a user's perspective. Based on a comprehensive review of the literature, 20 important IQ frameworks were identified. These models, though varied in their approach and application, share a number of characteristics regarding their classifications of the attributes of quality. The paper identifies common dimensions that exist across the existing IQ frameworks in the literature …

Mining Top-K Large Structural Patterns In A Massive Network, Feida Zhu, Qiang Qu, David Lo, Xifeng Yan, Jiawei Han, Philip S. Yu

Research Collection School Of Computing and Information Systems

With ever-growing popularity of social networks, web and bio-networks, mining large frequent patterns from a single huge network has become increasingly important. Yet the existing pattern mining methods cannot offer the efficiency desirable for large pattern discovery. We propose Spider- Mine, a novel algorithm to efficiently mine top-K largest frequent patterns from a single massive network with any user-specified probability of 1 − ϵ. Deviating from the existing edge-by-edge (i.e., incremental) pattern-growth framework, SpiderMine achieves its efficiency by unleashing the power of small patterns of a bounded diameter, which we call “spiders”. With the spider structure, our approach adopts a …

A Data-Intensive Approach To Named Entity Recognition Using Domain And Language Independent Methods, Olukayode Isaac Osesina

Theses and Dissertations

In this dissertation, I proposed a novel approach to Named Entity Recognition (NER) in which the contextual and intrinsic indicators are used for locating named entities and their semantic meanings in unstructured textual information (UTI). Named entity is the process of locating a word or a phrase that references a particular entity within a text. The data-intensive approach introduced in this dissertation departs from the traditional Natural Language Processing used in NER tasks in that it does not apply linguistic rules or knowledge in the entity recognition process. It leverages the wide availability of huge amounts of data as well …

Knowledge Discovery In Fetal Activity Data, Dallas H. Snider

Theses and Dissertations

The ability to determine accurately the health of a fetus through non-invasive techniques has tremendous positive affects for the fetus, the mother, and the health care system. In this project, Knowledge Discovery in Databases (KDD) techniques were applied to fetal magnetocardiogram data from 118 human fetuses with a gestational age of 24 to 39 weeks. These techniques produced three models relating to the health of a fetus which are presented in this document. The first model distinguished maternal high-risk factors versus low-risk factors. The second model was used to classify neonate outcomes of sick versus healthy. The third model was …

A Framework For Generating Data To Simulate Application Scoring, Kenneth Kennedy, Sarah Jane Delany, Brian Mac Namee

Conference papers

In this paper we propose a framework to generate artificial data that can be used to simulate credit risk scenarios. Artificial data is useful in the credit scoring domain for two reasons. Firstly, the use of artificial data allows for the introduction and control of variability that can realistically be expected to occur, but has yet to materialise in practice. The ability to control parameters allows for a thorough exploration of the performance of classification models under different conditions. Secondly, due to non-disclosure agreements and commercial sensitivities, obtaining real credit scoring data is a problematic and time consuming task. By …

Creating An International Joint Certificate In It Administration, Peter Wolcott

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

The University of Nebraska at Omaha (UNO) and the University of Agder (UiA), Norway, are collaborating on the creation of an undergraduate certificate in Information Technology Administration. The certificate is designed for students who are interested in managing the complex technical infrastructure of today's organizations. The certificate will consist of approximately 15 credit hours of hands-on courses, covering such areas as systems administration, network administration, database administration, security administration, and distributed systems. All courses will be offered online, using a variety of collaboration tools and teaching techniques that reflect the best of current practice. Students will take courses taught by …

Applying Data Mining Techniques To Evaluate Applications For Agricultural Loans, Emile J. Salame

Department of Agricultural Economics: Dissertations, Theses, and Student Research

Financial lending institutions continuously look at improving their credit risk models. This study examines the performance of three estimation methods: logistic regression, decision tree, and neural networks, in terms of their misclassification rates of credit default. The study uses 17,328 loans of grain producers for the period of 2006 - 2010. Those loans belong to the category of “diversified loans / core standard” originating from a large financial lending institution. The data has been split into nine different sets to acknowledge three factors: the shift in price of grains to a higher plateau after 2006, the contamination effect on defaulting …

Ccrank: Parallel Learning To Rank With Cooperative Coevolution, Shuaiqiang Wang, Byron J. Gao, Ke Wang, Hady W. Lauw

Research Collection School Of Computing and Information Systems

We propose CCRank, the first parallel algorithm for learning to rank, targeting simultaneous improvement in learning accuracy and efficiency. CCRank is based on cooperative coevolution (CC), a divide-and-conquer framework that has demonstrated high promise in function optimization for problems with large search space and complex structures. Moreover, CC naturally allows parallelization of sub-solutions to the decomposed subproblems, which can substantially boost learning efficiency. With CCRank, we investigate parallel CC in the context of learning to rank. Extensive experiments on benchmarks in comparison with the state-of-the-art algorithms show that CCRank gains in both accuracy and efficiency.

A Hubel Wiesel Model Of Early Concept Generalization Based On Local Correlation Of Input Features, Sepideh Sadeghi, Kiruthika Ramanathan

Research Collection School Of Computing and Information Systems

Hubel Wiesel models, successful in visual processing algorithms, have only recently been used in conceptual representation. Despite the biological plausibility of a Hubel-Wiesel like architecture for conceptual memory and encouraging preliminary results, there is no implementation of how inputs at each layer of the hierarchy should be integrated for processing by a given module, based on the correlation of the features. In our paper, we propose the input integration framework - a set of operations performed on the inputs to the learning modules of the Hubel Wiesel model of conceptual memory. These operations weight the modules as being general or …

Augmenting Online Learning With Real-Time Conferencing: Experiences From An International Course, Bjørn Erik Munkvold, Ilze Zigurs, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

This paper reports experiences from the use of real-time conferencing to support synchronous class interaction in an international online course. Through combination of video, audio, application sharing and chat, the students and instructors engaged in weekly interactions in a virtual classroom. This created an environment for rich interaction, augmenting the traditional use of course repositories. Further, this gave the students hands-on experience with real-time conferencing tools which are increasingly common in the workplace. The paper also discusses experienced challenges related to combining the use of multiple synchronous communication channels and presents implications for further use of real-time conferencing in online …

Network Security: Privacy-Preserving Data Publication: A Review On “Updates” In Continuous Data Publication, Adeel Anjum, Guillaume Raschia

International Conference on Information and Communication Technologies

Preserving the privacy of individuals while publishing their relevant data has been an important problem. Most of previous works in privacy preserving data publication focus on one time, static release of datasets. In multiple publications however, where data is published multiple times, these techniques are unable to ensure privacy of the concerned individuals as just joining either of the releases could result in identity disclosure. In this work, we tried to investigate the major findings in the scenario of continuous data publication, in which the data is not only published multiple times but also modified with INSERTS, UPDATES and DELETE …

Application Of Ict: Ascertaining Knowledge Flows Through Labor Mobility In The Ict Sector Of Pakistan, Abdul Baseer Qazi

International Conference on Information and Communication Technologies

This paper attempts to fill the gap in literature on channels of spillovers with a particular focus to the ICT sector and developing countries. With the help of a custom-made survey we have constructed variables which help to identify and measure the most prominent channels of spillovers suggested in literature. Our results corroborate labor mobility as one of the most important channel for inter-firm knowledge flows.

Artificial Intelligence - I: Adaptive Automated Teller Machines - Part Ii, Ghulam Mujtaba, Tariq Mahmood

International Conference on Information and Communication Technologies

Nowadays, the banking sector is increasingly relying on Automated Teller Machines (ATMs) in order to provide services to its customers. Although thousands of ATMs exist across many banks and different locations, the GUI and content of a typical ATM interface remains, more or less, the same. For instance, any ATM provides typical options for withdrawal, electronic funds transfer, viewing of mini-statements etc. However, such a static interface might not be suitable for all ATM customers, e.g., some users might not prefer to view all the options when they access the ATM, or to view specific withdrawal amounts less than, say, …

Artificial Intelligence – I: Adaptive Automated Teller Machines — Part I, Ghulam Mujtaba, Tariq Mahmood

International Conference on Information and Communication Technologies

During the past few years, the banking sector has started providing a variety of services to its customers. One of the most significant of such services has been the introduction of the Automated Teller Machines (ATMs) for providing online support to bank customers. The use of ATMs has reached its zenith in every developed country, and thousands of ATM transactions are occurring on a daily basis. In order to increase the customers' satisfaction and to provide them with more user-friendly ATM interfaces, it becomes important to mine the ATM transactions to discover useful patterns about the customers' interacting behaviors. In …

Evaluating And Implementing Web Scale Discovery Services: Part Two, Jason Vaughan, Tamera Hanken

Library Faculty Presentations

Part Four: Quick Tour of the Current Marketplace:

• "The Big 5"
• Similarities and differences

Part Five: It's Not All Sliced Bread:

• Shortcomings of web scale discovery

Part Six: Implementation (pre launch steps):

• Selecting and preparing implementation staff
• Preparing and communicating process/decisions with all staff
• Working with the vendor (roles, expectations, timeline)
• Workflow changes and implications (technical services)

Part Seven: Specific implementation tasks, issues, and considerations:

• Record loading and mapping (catalog content)
• Harvesting and mapping digital/local content
• Working with central index data (internal & external content)
• Web integration and customization
• Assessment and continuous improvement

Citizen Sensing: Opportunities And Challenges In Mining Social Signals And Perceptions, Amit P. Sheth

Kno.e.sis Publications

Millions of persons have become 'citizens' of an Internet- or Web-enabled social community. Web 2.0 fostered the open environment and applications for tagging, blogging, wikis, and social networking sites that have made information consumption, production, and sharing so incredibly easy. An interconnected network of people who actively observe, report, collect, analyze, and disseminate information via text, audio, or video messages, increasingly through pervasively connected mobile devices, has led to what we term citizen sensing. In this talk, we review recent progress in supporting collective intelligence through intelligent processing of citizen sensing. Key issues we cover in this talk are: - …

Evaluating And Implementing Web Scale Discovery Services: Part One, Jason Vaughan, Tamera Hanken

Library Faculty Presentations

Preface: Before Web Scale Discovery

• A very brief overview

Part 1: What is Web Scale Discovery

• Content
• Technology

Part 2: Why is Web Scale Discovery important?

• What’s the need?
• How is it different from earlier attempts at broad discovery?

Part 3: A Framework for Evaluating Web Scale Discovery Services

• What we did at UNLV
• Other options

Comparison Of Clustered Rdf Data Stores, Venkata Patchigolla

Purdue Polytechnic Masters Theses

Storing data in RDF format helps in simpler data interchange among different researchers compared to present approaches. There has been tremendous increase in the applications that use RDF data. The nature of RDF data is such that it tends to increase explosively. This makes it necessary to consider the time for retrieval and scalability of data while selecting a suitable RDF data store for developing applications. The research concentrates on comparing BigOWLIM. Bigdata, 4store and Virtuoso RDF stores on basis of their scalability and performance of storing and retrieving cancer proteomics and mass spectrometry data using SPARQL queries. In this …

Local Closed World Semantics: Keep It Simple, Stupid!, Adila Krishnadhi, Kunal Sengupta, Pascal Hitzler

Computer Science and Engineering Faculty Publications

A combination of open and closed-world reasoning (usually called local closed world reasoning) is a desirable capability of knowledge representation formalisms for Semantic Web applications. However, none of the proposals made to date for extending description logics with local closed world capabilities has had any significant impact on applications. We believe that one of the key reasons for this is that current proposals fail to provide approaches which are intuitively accessible for application developers at the same time are applicable, as extensions, to expressive description logics as SROIQ, which underlies the Web Ontology Language OWL.

In this paper, we propose …