Databases and Information Systems Commons^™

The Big Revolution: Future Potential Of Blockchain Technology, Sweksha Poudel, Sushant Bhatta, Jeremy Evert

Student Research

Blockchain is the continuation of humanity’s connection with technology. If we think back to a more ancient era, trade was done in a very informal manner. Often the result of one’s desire to get what they wanted was with violence. Society as a whole then started becoming more formalized and grew in complexity. Institutions like banks and governments established currency, policy, and regulation. Eventually, we had access to these same institutions on the internet and the list grew exponentially. Marketplaces like Amazon and eBay made trade much easier for the common man to use and it kept lowering uncertainties of …

The Role Of Ehealth In Disasters: A Strategy For Education, Training And Integration In Disaster Medicine, Anthony C. Norris, Jose J. Gonzalez, David T. Parry, Richard E. Scott, Julie Dugdale, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Publications

This paper describes the origins and progress of an international project to advance disaster eHealth (DEH) – the application of eHealth technologies to enhance the delivery of healthcare in disasters. The study to date has focused on two major themes; the role of DEH in facilitating inter-agency communication in disaster situations, and the fundamental need to promote awareness of DEH in the education of disaster managers and health professionals. The paper deals mainly with on-going research on the second of these themes, surveying the current provision of disaster medicine education, the design considerations for a DEH programme for health professionals, …

The Emergence Of Institutional Repositories: A Conceptual Understanding Of Key Issues Through Review Of Literature, O. P. Saini

Library Philosophy and Practice (e-journal)

It is the responsibility of the libraries to keep update its users by incorporating different technologies or tricks among the services offered to users. The libraries are managing diversified collection in both electronic and physical formats including the theses and dissertations awarded by their respective parent institutes in physical form. The academic libraries are directed by the Indian government through a mandate to protect and preserve the theses and dissertation in electronic form and provide access to the public domain. Institutional Repositories (IRs) have the perspective to store any amount of information electronically. Therefore, many of the academic libraries are …

Keep It Simple, Keep It Safe - Research On The Impacts Of Increasing Complexity Of Modern Enterprise Applications, Shawn Ware, David Phillips

UNO Student Research and Creative Activity Fair

As the Cybersecurity program within UNO continues to adapt to the ever-changing world of information systems and information security, the Cybersecurity Capstone has recently become an active, community-involvement project, where real-world organizations can receive valuable, useful research and information from students on their way towards a degree. This presentation encompasses two such projects from the Cybersecurity Capstone, looking at how modern, more complex systems can often increase system vulnerability.

Collecting And Organizing Far-Left Extremist Data From Unstructured Internet Sources, Eric Perez

UNO Student Research and Creative Activity Fair

Far-left extremism refers to a network of groups who adhere to and take direct action in accordance with one or more of the following ideas: Support for bio-centric diversity, the belief that the earth and animals are in immediate danger, and the view that the government and other parts of society are responsible for this danger and incapable/unwilling to fix the crisis and preserve the American wilderness (Chermak, Freilich, Duran, & Parkin). Far-left extremism groups self-report activities using publicly accessible, online communiqués. These activities include arson, property damage, harassment, sabotage, and theft (Loadenthal). The communiqués are structured like blog posts …

Cora: Commingled Remains And Analytics – An Open Community Ecosystem, Nicole Mcelroy, Ryan Ernst

UNO Student Research and Creative Activity Fair

Anthropologists at organizations such as the DPAA (Defense POW/MIA Accounting Agency) have the tough job of sorting through commingled remains of fallen soldiers. Under the direction of Professor Pawaskar at the College of IS&T, Ryan Ernst and I are currently developing a web application for the DPAA that will help them inventory the bones and record all the appropriate associations. After the inventory web application is built we will begin the analysis process using graph theory and other mathematical algorithms. This will ultimately help organizations like the DPAA get closer to the end goal of identifying fallen soldiers from commingled …

Explaining Social Recommendations To Casual Users: Design Principles And Opportunities, Chun-Hua Tsai, Peter Brusilovsky

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Recommender systems have become popular in recent years, and ordinary users are more likely to rely on such service when completing various daily tasks. The need to design and build explainable recommender interfaces is increasing rapidly. Most of the designs of such explanations are intended to reflect the underlying algorithms by which the recommendations are computed. These approaches have been shown to be useful for obtaining system transparency and trust. However, little is known about how to design explanation interfaces for causal (non-expert) users to achieve different explanatory goals. As a first step toward understanding the user interface design factors, …

The Cybher Program Supported By Cisse Framework To Engage And Anchor Middle-School Girls In Cybersecurity, Pamela Rowland

Masters Theses & Doctoral Dissertations

There is a piercing shortage of personnel in the cybersecurity field that will take several decades to accommodate. Despite being 50 percent of the workforce, females only account for 11 percent of the cybersecurity personnel. While efforts have been made to encourage more females into the field, more needs to be done. Reality shows that a change in the statistics is not taking place. Women remain seriously under-represented in cybersecurity degree programs and the workforce.

Prior research shows that elementary girls are equally as interested in the cyber path as boys. It is in middle school that this interest shifts, …

Automatic Persona Generation (Apg): A Rationale And Demonstration, Soon-Gyo Jung, Joni Salminen, Haewoon Kwak, Jisun An, Bernard J Jansen

Research Collection School Of Computing and Information Systems

We present Automatic Persona Generation (APG), a methodology and system for quantitative persona generation using large amounts of online social media data. The system is operational, beta deployed with several client organizations in multiple industry verticals and ranging from small-to-medium sized enterprises to large multi-national corporations. Using a robust web framework and stable back-end database, APG is currently processing tens of millions of user interactions with thousands of online digital products on multiple social media platforms, such as Facebook and YouTube. APG identifies both distinct and impactful user segments and then creates persona descriptions by automatically adding pertinent features, such …

Towards Practical Privacy-Preserving Analytics For Iot And Cloud Based Healthcare Systems, Sagar Sharma, Keke Chen, Amit P. Sheth

Kno.e.sis Publications

Modern healthcare systems now rely on advanced computing methods and technologies, such as IoT devices and clouds, to collect and analyze personal health data at unprecedented scale and depth. Patients, doctors, healthcare providers, and researchers depend on analytical models derived from such data sources to remotely monitor patients, early-diagnose diseases, and find personalized treatments and medications. However, without appropriate privacy protection, conducting data analytics becomes a source of privacy nightmare. In this paper, we present the research challenges in developing practical privacy-preserving analytics in healthcare information systems. The study is based on kHealth - a personalized digital healthcare information system …

Building Trust In Artificial Intelligence, Machine Learning, And Robotics, Keng Siau, Weiyu Wang

Research Collection School Of Computing and Information Systems

In this article, we look at trust in artificial intelligence, machine learning (ML), and robotics. We first review the concept of trust in AI and examine how trust in AI may be different from trust in other technologies. We then discuss the differences between interpersonal trust and trust in technology and suggest factors that are crucial in building initial trust and developing continuous trust in artificial intelligence.

Do Your Friends Make You Buy This Brand?: Modeling Social Recommendation With Topics And Brands, Minh Duc Luu, Ee Peng Lim

Research Collection School Of Computing and Information Systems

Consumer behavior and marketing research have shown that brand has significant influence on product reviews and product purchase decisions. However, there is very little work on incorporating brand related factors into product recommender systems. Meanwhile, the similarity in brand preference between a user and other socially connected users also affects her adoption decisions. To integrate seamlessly the individual and social brand related factors into the recommendation process, we propose a novel model called Social Brand–Item–Topic (SocBIT). As the original SocBIT model does not enforce non-negativity, which poses some difficulty in result interpretation, we also propose a non-negative version, called SocBIT(Formula …

The Pharmacogene Variation (Pharmvar) Consortium: Incorporation Of The Human Cytochrome P450 (Cyp) Allele Nomenclature Database, Andrea Gaedigk, Magnus Ingelman-Sundberg, Neil A. Miller, J Steven Leeder, Michelle Whirl-Carrillo, Teri E. Klein

Manuscripts, Articles, Book Chapters and Other Papers

The Human Cytochrome P450 (CYP) Allele Nomenclature Database, a critical resource to the pharmacogenetics and genomics communities, will be transitioning to the Pharmacogene Variation (PharmVar) Consortium. In this report we provide a summary of the current database, provide an overview of the PharmVar consortium and highlight the PharmVar database which will serve as the new home for pharmacogene nomenclature.

An Lstm Model For Cloze-Style Machine Comprehension, Shuohang Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Machine comprehension is concerned with teaching machines to answer reading comprehension questions. In this paper we adopt an LSTM-based model we designed earlier for textual entailment and propose two new models for cloze-style machine comprehension. In our first model, we treat the document as a premise and the question as a hypothesis, and use an LSTM with attention mechanisms to match the question with the document. This LSTM remembers the best answer token found in the document while processing the question. Furthermore, we observe some special properties of machine comprehension and propose a two-layer LSTM model. In this model, we …

Mining Sandboxes: Are We There Yet?, Lingfeng Bao, Tien Duy B. Le, David Lo

Research Collection School Of Computing and Information Systems

The popularity of Android platform on mobile devices has attracted much attention from many developers and researchers, as well as malware writers. Recently, Jamrozik et al. proposed a technique to secure Android applications referred to as mining sandboxes. They used an automated test case generation technique to explore the behavior of the app under test and then extracted a set of sensitive APIs that were called. Based on the extracted sensitive APIs, they built a sandbox that can block access to APIs not used during testing. However, they only evaluated the proposed technique with benign apps but not investigated whether …

Urlnet: Learning A Url Representation With Deep Learning For Malicious Url Detection, Hung Le, Hong Quang Pham, Doyen Sahoo, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Malicious URLs host unsolicited content and are used to perpetrate cybercrimes. It is imperative to detect them in a timely manner. Traditionally, this is done through the usage of blacklists, which cannot be exhaustive, and cannot detect newly generated malicious URLs. To address this, recent years have witnessed several efforts to perform Malicious URL Detection using Machine Learning. The most popular and scalable approaches use lexical properties of the URL string by extracting Bag-of-words like features, followed by applying machine learning models such as SVMs. There are also other features designed by experts to improve the prediction performance of the …

A Model Of Competition Between Perpetual Software And Software As A Service, Zhiling Guo, Dan Ma

Research Collection School Of Computing and Information Systems

Duplicate record, see https://ink.library.smu.edu.sg/sis_research/3744/. Software as a service (SaaS) has grown to be a significant segment of many software product markets. SaaS vendors, which charge customers based on use and continuously improve the quality of their products, have put competitive pressure on traditional perpetual software vendors, which charge a licensing fee and periodically upgrade the quality of their software. We develop an analytical model to study the competitive pricing strategies of an incumbent perpetual software vendor in the presence of a SaaS competitor. We find that, depending on both the SaaS quality improvement rate and the network effect, the …

A Model Of Competition Between Perpetual Software And Software As A Service, Zhiling Guo, Dan Ma

Research Collection School Of Computing and Information Systems

Software as a service (SaaS) has grown to be a significant segment of many software product markets. SaaS vendors, which charge customers based on use and continuously improve the quality of their products, have put competitive pressure on traditional perpetual software vendors, which charge a licensing fee and periodically upgrade the quality of their software. We develop an analytical model to study the competitive pricing strategies of an incumbent perpetual software vendor in the presence of a SaaS competitor. We find that, depending on both the SaaS quality improvement rate and the network effect, the perpetual software vendor adopts one …

Attributed Social Network Embedding, Lizi Liao, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Embedding network data into a low-dimensional vector space has shown promising performance for many real-world applications, such as node classification and entity retrieval. However, most existing methods focused only on leveraging network structure. For social networks, besides the network structure, there also exists rich information about social actors, such as user profiles of friendship networks and textual content of citation networks. These rich attribute information of social actors reveal the homophily effect, exerting huge impacts on the formation of social networks. In this paper, we explore the rich evidence source of attributes in social networks to improve network embedding. We …

Visualizing Research Impact Through Citation Data, Yong Wang, Conglei Shi, Liangyue Li, Hanghang Tong, Huamin Qu

Research Collection School Of Computing and Information Systems

Research impact plays a critical role in evaluating the research quality and influence of a scholar, a journal, or a conference. Many researchers have attempted to quantify research impact by introducing different types of metrics based on citation data, such as h-index, citation count, and impact factor. These metrics are widely used in the academic community. However, quantitative metrics are highly aggregated in most cases and sometimes biased, which probably results in the loss of impact details that are important for comprehensively understanding research impact. For example, which research area does a researcher have great research impact on? How does …

A Modified Balcik Last Mile Distribution Model For Relief Operations Using Open Road Networks, Lance L. Putong, Marlene M. De Leon

Department of Information Systems & Computer Science Faculty Publications

The last mile in disaster relief distribution chain is the delivery of goods from a central warehouse to the evacuation centers assigned for a given area. Its effectiveness relies on the proper allocation of each kind of relief good amongst the demand areas on a given frequency. Because these operations involve a limited supply of relief goods, vehicles, and time, it is important to optimize these operations to satisfy as much demand as possible. The study aims to create a linear programming model which provides a set of recommendations on how the current disaster relief supply chain may be carried …

Sparse Passive-Aggressive Learning For Bounded Online Kernel Methods, Jing Lu, Doyen Sahoo, Peilin Zhao, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

One critical deficiency of traditional online kernel learning methods is their unbounded and growing number of support vectors in the online learning process, making them inefficient and non-scalable for large-scale applications. Recent studies on scalable online kernel learning have attempted to overcome this shortcoming, e.g., by imposing a constant budget on the number of support vectors. Although they attempt to bound the number of support vectors at each online learning iteration, most of them fail to bound the number of support vectors for the final output hypothesis, which is often obtained by averaging the series of hypotheses over all the …

Unified Locally Linear Classifiers With Diversity-Promoting Anchor Points, Chenghao Liu, Teng Zhang, Peilin Zhao, Jianling Sun, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Locally Linear Support Vector Machine (LLSVM) has been actively used in classification tasks due to its capability of classifying nonlinear patterns. However, existing LLSVM suffers from two drawbacks: (1) a particular and appropriate regularization for LLSVM has not yet been addressed; (2) it usually adopts a three-stage learning scheme composed of learning anchor points by clustering, learning local coding coordinates by a predefined coding scheme, and finally learning for training classifiers. We argue that this decoupled approaches oversimplifies the original optimization problem, resulting in a large deviation due to the disparate purpose of each step. To address the first issue, …

Things You May Not Know About Android (Un)Packers: A Systematic Study Based On Whole-System Emulation, Yue Duan, Mu Zhang, Abhishek Vasist Bhaskar, Heng Yin, Xiaorui Pan, Tongxin Li, Xueqiang Wang, Xiaofeng Wang

Research Collection School Of Computing and Information Systems

The prevalent usage of runtime packers has complicated Android malware analysis, as both legitimate and malicious apps are leveraging packing mechanisms to protect themselves against reverse engineer. Although recent efforts have been made to analyze particular packing techniques, little has been done to study the unique characteristics of Android packers. In this paper, we report the first systematic study on mainstream Android packers, in an attempt to understand their security implications. For this purpose, we developed DROIDUNPACK, a whole-system emulation based Android packing analysis framework, which compared with existing tools, relies on intrinsic characteristics of Android runtime (rather than heuristics), …

Attribute-Based Cloud Storage With Secure Provenance Over Encrypted Data, Hui Cui, Robert H. Deng, Yingjiu Li

Research Collection School Of Computing and Information Systems

To securely and conveniently enjoy the benefits of cloud storage, it is desirable to design a cloud data storage system which protects data privacy from storage servers through encryption, allows fine-grained access control such that data providers can expressively specify who are eligible to access the encrypted data, enables dynamic user management such that the total number of data users is unbounded and user revocation can be carried out conveniently, supports data provider anonymity and traceability such that a data provider’s identity is not disclosed to data users in normal circumstances but can be traced by a trusted authority if …

Upping The Game Of Taxi Driving In The Age Of Uber, Shashi Shekhar Jha, Shih-Fen Cheng, Meghna Lowalekar, Wai Hin Wong, Rajendram Rishikeshan Rajendram, Trong Khiem Tran, Pradeep Varakantham, Nghia Truong Trong, Firmansyah Abd Rahman

Research Collection School Of Computing and Information Systems

In most cities, taxis play an important role in providing point-to-point transportation service. If the taxi service is reliable, responsive, and cost-effective, past studies show that taxi-like services can be a viable choice in replacing a significant amount of private cars. However, making taxi services efficient is extremely challenging, mainly due to the fact that taxi drivers are self-interested and they operate with only local information. Although past research has demonstrated how recommendation systems could potentially help taxi drivers in improving their performance, most of these efforts are not feasible in practice. This is mostly due to the lack of …

Modelling Domain Relationships For Transfer Learning On Retrieval-Based Question Answering Systems In E-Commerce, Jianfei Yu, Minghui Qiu, Jing Jiang, Jun Huang, Shuangyong Song, Wei Chu, Haiqing Chen

Research Collection School Of Computing and Information Systems

Nowadays, it is a heated topic for many industries to build automatic question-answering (QA) systems. A key solution to these QA systems is to retrieve from a QA knowledge base the most similar question of a given question, which can be reformulated as a paraphrase identification (PI) or a natural language inference (NLI) problem. However, most existing models for PI and NLI have at least two problems: They rely on a large amount of labeled data, which is not always available in real scenarios, and they may not be efficient for industrial applications. In this paper, we study transfer learning …

Integrated Cooperation And Competition In Multi-Agent Decision-Making, Kyle Hollins Wray, Akshat Kumar, Shlomo Zilberstein

Research Collection School Of Computing and Information Systems

Observing that many real-world sequential decision problems are not purely cooperative or purely competitive, we propose a new model—cooperative-competitive process (CCP)—that can simultaneously encapsulate both cooperation and competition.First, we discuss how the CCP model bridges the gap between cooperative and competitive models. Next, we investigate a specific class of group-dominant CCPs, in which agents cooperate to achieve a common goal as their primary objective, while also pursuing individual goals as a secondary objective. We provide an approximate solution for this class of problems that leverages stochastic finite-state controllers.The model is grounded in two multi-robot meeting and box pushing domains that …

R3: Reinforced Ranker-Reader For Open-Domain Question Answering, Shuohang Wang, Mo Yu, Xiaoxiao Guo, Zhiguo Wang, Tim Klinger, Wei Zhang, Shiyu Chang, Gerald Tesauro, Bowen Zhou, Jing Jiang

Research Collection School Of Computing and Information Systems

In recent years researchers have achieved considerable success applying neural network methods to question answering (QA). These approaches have achieved state of the art results in simplified closed-domain settings such as the SQuAD (Rajpurkar et al. 2016) dataset, which provides a pre-selected passage, from which the answer to a given question may be extracted. More recently, researchers have begun to tackle open-domain QA, in which the model is given a question and access to a large corpus (e.g., wikipedia) instead of a pre-selected passage (Chen et al. 2017a). This setting is more complex as it requires large-scale search for relevant …

Identifying Self-Admitted Technical Debt In Open Source Projects Using Text Mining, Qiao Huang, Emad Shihab, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Technical debt is a metaphor to describe the situation in which long-term code quality is traded for short-term goals in software projects. Recently, the concept of self-admitted technical debt (SATD) was proposed, which considers debt that is intentionally introduced, e.g., in the form of quick or temporary fixes. Prior work on SATD has shown that source code comments can be used to successfully detect SATD, however, most current state-of-the-art classification approaches of SATD rely on manual inspection of the source code comments. In this paper, we proposed an automated approach to detect SATD in source code comments using text mining. …