Databases and Information Systems Commons^™

On Predicting User Affiliations Using Social Features In Online Social Networks, Minh Thap Nguyen

Dissertations and Theses Collection (Open Access)

User profiling such as user affiliation prediction in online social network is a challenging task, with many important applications in targeted marketing and personalized recommendation. The research task here is to predict some user affiliation attributes that suggest user participation in different social groups.

Time-Series Data Mining In Transportation: A Case Study On Singapore Public Train Commuter Travel Patterns, Tin Seong Kam, Roy Ka Wei Lee

Research Collection School Of Computing and Information Systems

The adoption of smart cards technologies and automated data collection systems (ADCS) in transportation domain had provided public transport planners opportunities to amass a huge and continuously increasing amount of time-series data about the behaviors and travel patterns of commuters. However the explosive growth of temporal related databases has far outpaced the transport planners’ ability to interpret these data using conventional statistical techniques, creating an urgent need for new techniques to support the analyst in transforming the data into actionable information and knowledge. This research study thus explores and discusses the potential use of time-series data mining, a relatively new …

Information-Theoretic Multi-View Domain Adaptation: A Theoretical And Empirical Study, Pei Yang, Wei Gao

Research Collection School Of Computing and Information Systems

Multi-view learning aims to improve classification performance by leveraging the consistency among different views of data. The incorporation of multiple views was paid little attention in the studies of domain adaptation, where the view consistency based on source data is largely violated in the target domain due to the distribution gap between different domain data. In this paper, we leverage multiple views for cross-domain document classification. The central idea is to strengthen the views' consistency on target data by identifying the associations of domain-specific features from different domains. We present an Information-theoretic Multi-view Adaptation Model (IMAM) using a multi-way clustering …

Online Feature Selection And Its Applications, Jialei Wang, Peilin Zhao, Steven C. H. Hoi, Rong Jin

Research Collection School Of Computing and Information Systems

Feature selection is an important technique for data mining. Despite its importance, most studies of feature selection are restricted to batch learning. Unlike traditional batch learning methods, online learning represents a promising family of efficient and scalable machine learning algorithms for large-scale applications. Most existing studies of online learning require accessing all the attributes/features of training instances. Such a classical setting is not always appropriate for real-world applications when data instances are of high dimensionality or it is expensive to acquire the full set of attributes/features. To address this limitation, we investigate the problem of online feature selection (OFS) in …

L-Opacity: Linkage-Aware Graph Anonymization, Sadegh Nobari, Panagiotis Karras, Hwee Hwa Pang, Stephane Bressan

Research Collection School Of Computing and Information Systems

The wealth of information contained in online social networks has created a demand for the publication of such data as graphs. Yet, publication, even after identities have been removed, poses a privacy threat. Past research has suggested ways to publish graph data in a way that prevents the re-identification of nodes. However, even when identities are effectively hidden, an adversary may still be able to infer linkage between individuals with sufficiently high confidence. In this paper, we focus on the privacy threat arising from such link disclosure. We suggest L-opacity, a sufficiently strong privacy model that aims to control an …

The Adoption Of E-Learning Systems In Low Income Countries: The Case Of Ethiopia, Yonas Hagos, Solomon Negash

Faculty Articles

This paper presents the Technology Acceptance Model (TAM) to examine the adoption of e-learning system in low-income countries, the case of Ethiopia. The research uses a quantitative research approach to examine Ethiopian tertiary level distance students’ determinant factors for the acceptance of e-learning systems. A questionnaire-based survey was conducted to collect data from 255 undergraduate distance learners in a higher education institute in Ethiopia. The data were analyzed using the Structural Equation Modeling (SEM) (Hair et al, 2005) technique to examine the causal model. The results indicated that perceived usefulness and perceived ease of use significantly affected distance learners’ behavioral …

A Computational Approach To Qualitative Analysis In Large Textual Datasets, Michael Evans

Dartmouth Scholarship

In this paper I introduce computational techniques to extend qualitative analysis into the study of large textual datasets. I demonstrate these techniques by using probabilistic topic modeling to analyze a broad sample of 14,952 documents published in major American newspapers from 1980 through 2012. I show how computational data mining techniques can identify and evaluate the significance of qualitatively distinct subjects of discussion across a wide range of public discourse. I also show how examining large textual datasets with computational methods can overcome methodological limitations of conventional qualitative methods, such as how to measure the impact of particular cases on …

Comparative Trust Management With Applications: Bayesian Approaches Emphasis, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Trust relationships occur naturally in many diverse contexts such as collaborative systems, e-commerce, interpersonal interactions, social networks, and semantic sensor web. As agents providing content and services become increasingly removed from the agents that consume them, the issue of robust trust inference and update becomes critical. There is a need to find online substitutes for traditional (direct or face-to-face) cues to derive measures of trust, and create efficient and robust systems for managing trust in order to support decision-making. Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its …

Cursing In English On Twitter, Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated through highly connected social network. Will these distinctive features of social media lead to a change in people's cursing behavior? In this paper, we examine the characteristics of cursing activity on a popular social media platform - Twitter, involving the analysis of …

Social Correlation In Latent Spaces For Complex Networks, Freddy Chong Tat Chua

Dissertations and Theses Collection (Open Access)

This dissertation addresses the subject of measuring social correlation among users within a complex social network. Social correlation is closely related to the measurement of social influence in social sciences. While social influence focuses on the existence of causal influence among users, we take a computational approach to measure correlation strength among users based on their shared interactions. We call this social correlation. To formally model social correlation, we propose a framework which contains two major parts. The first part is that of representing users behavior in a computationally efficient and accurate manner. For example, social media users perform many …

Unstructured P2p Link Lifetimes Redux, Zhongmei Yao, Daren B. H. Cline

Computer Science Faculty Publications

We revisit link lifetimes in random P2P graphs under dynamic node failure and create a unifying stochastic model that generalizes the majority of previous efforts in this direction. We not only allow nonexponential user lifetimes and age-dependent neighbor selection, but also cover both active and passive neighbor-management strategies, model the lifetimes of incoming and outgoing links, derive churn-related message volume of the system, and obtain the distribution of transient in/out degree at each user. We then discuss the impact of design parameters on overhead and resilience of the network.

Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li

Research Collection School Of Computing and Information Systems

Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results: This work proposes a new method, β ACV ASA , to predict the change of binding free energy after alanine mutations. β ACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector …

Representative Discovery Of Structure Cues For Weakly-Supervised Image Segmentation, Luming Zhang, Yue Gao, Yingjie Xia, Ke Lu, Jialie Shen, Rongrong Ji

Research Collection School Of Computing and Information Systems

Weakly-supervised image segmentation is a challenging problem with multidisciplinary applications in multimedia content analysis and beyond. It aims to segment an image by leveraging its imagelevel semantics (i.e., tags). This paper presents a weakly-supervised image segmentation algorithm that learns the distribution of spatially structural superpixel sets from image-level labels. More specifically, we first extract graphlets from a given image, which are small-sized graphs consisting of superpixels and encapsulating their spatial structure. Then, an ecient manifold embedding algorithm is proposed to transfer labels from training images into graphlets. It is further observed that there are numerous redundant graphlets that are not …

Integrating Water Exclusion Theory Into Β Contacts To Predict Binding Free Energy Changes And Binding Hot Spots, Qian Liu, Steven C. H. Hoi, Chee Keong Kwoh, Limsoon Wong, Jinyan Li

Research Collection School Of Computing and Information Systems

Binding free energy and binding hot spots at protein-protein interfaces are two important research areas for understanding protein interactions. Computational methods have been developed previously for accurate prediction of binding free energy change upon mutation for interfacial residues. However, a large number of interrupted and unimportant atomic contacts are used in the training phase which caused accuracy loss. Results: This work proposes a new method, β ACV ASA , to predict the change of binding free energy after alanine mutations. β ACV ASA integrates accessible surface area (ASA) and our newly defined β contacts together into an atomic contact vector …

Democracy Is Good For Ranking: Towards Multi-View Rank Learning And Adaptation In Web Search, Wei Gao, Pei Yang

Research Collection School Of Computing and Information Systems

No abstract provided.

Libol: A Library For Online Learning Algorithms, Steven C. H. Hoi, Jialei Wang, Peilin Zhao

Research Collection School Of Computing and Information Systems

LIBOL is an open-source library for large-scale online learning, which consists of a large family of efficient and scalable state-of-the-art online learning algorithms for large- scale online classification tasks. We have offered easy-to-use command-line tools and examples for users and developers, and also have made comprehensive documents available for both beginners and advanced users. LIBOL is not only a machine learning toolbox, but also a comprehensive experimental platform for conducting online learning research.

Extended Comprehensive Study Of Association Measures For Fault Localization, Lucia Lucia, David Lo, Lingxiao Jiang, Ferdian Thung, Aditya Budi

Research Collection School Of Computing and Information Systems

Spectrum-based fault localization is a promising approach to automatically locate root causes of failures quickly. Two well-known spectrum-based fault localization techniques, Tarantula and Ochiai, measure how likely a program element is a root cause of failures based on profiles of correct and failed program executions. These techniques are conceptually similar to association measures that have been proposed in statistics, data mining, and have been utilized to quantify the relationship strength between two variables of interest (e.g., the use of a medicine and the cure rate of a disease). In this paper, we view fault localization as a measurement of the …

Predicting Response In Mobile Advertising With Hierarchical Importance-Aware Factorization Machine, Richard Jayadi Oentaryo, Ee Peng Lim, Jia Wei Low, David Lo, Michael Finegold

Research Collection School Of Computing and Information Systems

Mobile advertising has recently seen dramatic growth, fueled by the global proliferation of mobile phones and devices. The task of predicting ad response is thus crucial for maximizing business revenue. However, ad response data change dynamically over time, and are subject to cold-start situations in which limited history hinders reliable prediction. There is also a need for a robust regression estimation for high prediction accuracy, and good ranking to distinguish the impacts of different ads. To this end, we develop a Hierarchical Importance-aware Factorization Machine (HIFM), which provides an effective generic latent factor framework that incorporates importance weights and hierarchical …

Digital Certificate Management: Optimal Pricing And Crl Releasing Strategies, Jie Zhang, Nan Hu, M. K. Raka

Research Collection School Of Computing and Information Systems

The fast growth of e-commerce and online activities places increasing needs for authentication and secure communication to enable information exchange and online transactions. The public key infrastructure (PKI) provides a promising foundation for meeting such demand, in which certificate authorities (CAs) provide digital certificates. In practice, it is critical to understand consumer purchasing and revocation behaviors so that CAs can better manage the digital certificates and its CRL releasing process. To address this problem, we analytically model a CA's pricing and revocation releasing strategies taking into consideration the users' rational decisions. The model provides solutions two main research questions: (1) …

Increasing Adolescent Interest In Computing Through The Use Of Social Cognitive Career Theory, Osama Eljabiri

Dissertations

While empirical research efforts are sufficient to provide evidence of the role of most constructs in the Social Cognitive Career Theory (SCCT), this dissertation shifts the research focus and finds serious shortcomings in defining the construct of computer technology learning experiences design.

The purpose of this dissertation is to investigate whether, and to what extent, the proposed SCCT-enhanced framework can increase self-efficacy and interest of pre-college and college students in computer-based technology through the newly proposed “Learning Experiences” construct; in particular, whether it can reduce the gender gaps.

As a result of a comprehensive literature review, the dissertation connects learning, …

Svmaud: Using Textual Information To Predict The Audience Level Of Written Works Using Support Vector Machines, Todd Will

Dissertations

Information retrieval systems should seek to match resources with the reading ability of the individual user; similarly, an author must choose vocabulary and sentence structures appropriate for his or her audience. Traditional readability formulas, including the popular Flesch-Kincaid Reading Age and the Dale-Chall Reading Ease Score, rely on numerical representations of text characteristics, including syllable counts and sentence lengths, to suggest audience level of resources. However, the author’s chosen vocabulary, sentence structure, and even the page formatting can alter the predicted audience level by several levels, especially in the case of digital library resources. For these reasons, the performance of …

Rethinking Fs-Isac: An It Security Information Sharing Network Model For The Financial Services Sector, Charles Zhechao Liu, Humayun Zafar, Yoris A. Au

Faculty Articles

This study examines a critical incentive alignment issue facing FS-ISAC (the information sharing alliance in the financial services industry). Failure to encourage members to share their IT security-related information has seriously undermined the founding rationale of FS-ISAC. Our analysis shows that many information sharing alliances’ membership policies are plagued with the incentive misalignment issue and may result in a “free-riding” or “no information sharing” equilibrium. To address this issue, we propose a new information sharing membership policy that incorporates an insurance option and show that the proposed policy can align members’ incentives and lead to a socially optimal outcome. Moreover, …

Advances In Documentation, Digital Curation, Virtual Exhibition, And A Test Of 3d Geometric Morhpometrics: A Case Study Of The Vanderpool Vessels From The Ancestral Caddo Territory, Robert Z. Selden Jr., Timothy K. Perttula, Michael J. O'Brien

CRHR: Archaeology

Three-dimensional (3D) digital scanning of archaeological materials is typically used as a tool for artifact documentation. With the permission of the Caddo Nation of Oklahoma, 3D documentation of Caddo funerary vessels from the Vanderpool site (41SM77) was conducted with the initial goal of ensuring that these data would be publicly available for future research long after the vessels were repatriated. A digital infrastructure was created to archive and disseminate the resultant 3D datasets, ensuring that they would be accessible by both researchers and the general public (CRHR 2014a). However, 3D imagery can be used for much more than documentation. To …

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 …

Decrease In Free Computer Science Papers Found Through Google Scholar, Lee A. Pedersen, Julie Arendt

VCU Libraries Faculty and Staff Publications

Purpose - Google Scholar was used to locate free full-text versions of computer science research papers to determine what proportion could be freely accessed.
Design/methodology/approach - A sample of 1967 conference papers and periodical articles from 2003-2010, indexed in the ACM Guide to Computing Literature, was searched for manually in Google Scholar, using the paper or article title and the first author’s surname and supplementary searches as needed.
Findings - Free full-text versions were found for 52% of the conference papers and 55% of the periodical articles. Documents with older publication dates were more likely to be freely accessible than …

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.

A Comparative Review Of Information Technology Project Management In Private And Public Sector Organization, Muhammad Obeidat, Max North

Faculty Articles

Both private and public sector organizations tend to recognize the prominence of information technology within project management techniques and practices. The primary objective of this paper is to present a comparative review of information technology within project management in private and public sectors. Moreover, this research provides an extensive review of related topics such as the evolution of information technology, factors contributing to project abandonment, and the tools and techniques of management that effect project success. In conclusion, the authors present a variety of practical and effective guidelines and recommend approaches for the successful deployment of information technology within project …

Networks Of Users And Powers: Blackboard Software Roadmap As Cultural Practice, Diana Gellci

Wayne State University Dissertations

With the rapid growth of eLearning applications - the software providing for learning through the Internet - it has become commonplace to describe those technologies as both simple tools and user-friendly. These two vague yet suggestive terms make the operating of the technology appear as social value and any related issues as a user's problem. Interested neo-liberal groups take a step further when considering eLearning technologies as the solution for the problems faced in the field. STS studies recognize that technology fetishism is strategically employed to justify the latest developments of capitalism as technological and logical.

This doctoral study examines …

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 …

Virtualization-Based System Hardening Against Untrusted Kernels, Yueqiang Cheng

Dissertations and Theses Collection (Open Access)

Applications are integral to our daily lives to help us processing sensitive I/O data, such as individual passwords and camera streams, and private application data, such as financial information and medical reports. However, applications and sensitive data all surfer from the attacks from kernel rootkits in the traditional architecture, where the commodity OS that is supposed to be the secure foothold of the system is routinely compromised due to the large code base and the broad attack surface. Fortunately, the virtualization technology has significantly reshaped the landscape of the modern computer system, and provides a variety of new opportunities for …